This work allows me to make intelligent decisions about what is being offered as historical donations and to proactively collect, filling in the gaps in the collection so that researchers have what they need to interpret the past. In this role, I was able to play a key part in collecting the Lisa source code and making it available to the public.

Software Curator Al Kossow with the Lisa. Kossow is the Robert N. Miner Software Curator and is responsible for collecting historical software and developing tools for reading and preserving CHM’s software artifacts.

Why is the Lisa source code important?

The source code is a snapshot of an entire product, in its final form, first proposed in 1978 and shipped in 1983. The Lisa didn’t follow the usual path of Apple products. It was envisioned as a turnkey solution for business, something Apple had little experience in doing, and it was developed by management trained in the “HP Way.”

Ultimately, the UI development, system tools, and some portions of the code created for Lisa made it into the mainstream, when it was used to accelerate the development of the Macintosh.

Honestly, it’s hard to think of some new hook or anecdote that hasn’t been told literally for decades about Lisa and its place in Apple’s history. But what might surprise you is that there is still so much to discover about this time in Apple’s history. Here’s a little bit about what I have uncovered in my research and what I still hope to discover, hopefully with your help.

Back in October, 1986, long before I became a curator at the Computer History Museum, I responded to a job ad for a software engineer posted on the Usenet group ba.jobs from the legendary Al Alcorn. I didn’t know it when I applied, but Al was an Apple Fellow in a not-well-known part of the company known as the Advanced Technology Group (ATG). There were never many Apple Fellows, and they were all highly respected people who were allowed to work on whatever they wanted. When I started, for example, Lisa and Macintosh cocreator Bill Atkinson was working on a project called “Wildcard,” which became HyperCard.

After I was in ATG for a while, I wanted to learn about its history. It turned out that after the Lisa and Mac groups merged, Wayne Rosing, general manager of the Lisa group after John Couch’s departure, ran a group of people known as the Education Research Group (ERG). When Wayne left for Sun, Xerox PARC alum and former Lisa applications manager Larry Tesler took over the group, and as its charter expanded ERG became ATG. Some of the early ATG history is included in an oral history I recorded with Larry in 2013, which you can read here.

Managers of the Lisa development group. From left to right: John Couch (VP and General Manager of the Lisa division), Bruce Daniels (software, systems architecture), Wayne Rosing (hardware, later all of Lisa engineering), Larry Tesler (applications software and libraries, user interface design and testing). Photo by Lee Youngblood. Scan of page 88 of Personal Computing Magazine, February 1983, CHM #102661079.

In the mid-’80s, ATG was supposed to be Apple’s project incubator. The plan was that as new technologies were created, they would be handed off to Product Development along with the staff. With a few notable exceptions (the people in the ATG Graphics and Sound Group) that never really happened. A whole book could be written on ATG. Maybe someone will do that someday, and the oral history I did with Larry here at CHM could help with that. In my oral histories, I try to cover topics that don’t appear in the preexisting literature.

What does this have to do with Lisa?

There were a LOT of ex-Lisa people in ATG. I heard first-hand about the Lisa OS and applications from the people who wrote them. But although I tried to find someone who would allow me to see the source code, I still had not succeeded by the time I resigned from Apple and joined CHM in 2005.

When Steve Jobs gave CHM permission to release the QuickDraw source code things changed. Now, there was an approval process for getting historical Apple source code released for people to study.

I asked Chris Espinosa, one of Apple’s earliest and longest-serving employees, who I had known since the 1980s, if it would be possible to recover the Lisa source code. After some searching, he was able to find it in the source control offsite archives, and I recovered the data on one of the Macs in my software lab at CHM. The code was translated from its original format to one easier to view on a 2020s computer, and it has now been made available for you to study here.

Chris Espinosa, Apple employee number eight, was instrumental in providing CHM with the Lisa source code. Shown here, Chris with software curator Al Kossow, holding the Apple II heuristics Speechlab card at the Apple “Twiggy Mac Day” event organized by Dan Kottke at the Computer History Museum in September 12, 2013.

Looking at the code in 2023, its structure is somewhat opaque. Fortunately, the web has established worldwide instantaneous connectivity and sharing of the primary documentation sources that have been collected about the system over the decades along with functional Lisa computer emulators. As a result, I’m hoping that a dialog will start about this historical artifact and fill in some of the pieces of the Lisa story that are still missing.

In the meantime, here’s a bit of high-level Lisa software history, and some theories about why the system looks the way that it does.

Lisa’s Roots

The hardware and software of the Lisa didn’t spring fully formed from the work done at Apple. Unlike the Apple II before it, the company had hired engineers and management experienced in minicomputer design for the development of the Lisa Office System product.

Many were from HP’s General Systems Division in the Santa Clara Valley, where the HP3000 and 300 computers were developed. They brought experience with developing operating systems and software in a high-level language and also provided a framework for the structure of the system. It is my opinion that the HP300 Amigo had a huge influence on Lisa.

The Amigo was a business minicomputer designed to compete with IBM’s System 34. It had an integrated display with application-programmable “soft switches” to the right of the wide CRT display, and internal hard and floppy disks and was announced in late 1978.

The problem was that with a base price of $36,500 the Amigo was expensive and considered a product failure. Later machines based on it (the HP250 and 260) were successful in Europe.

Unfortunately, my attempts to interview people directly involved in the engineering management and implementation of the Amigo and the Lisa have never been accepted. Hopefully, the code release will provide stimulus for new information and documentation of Lisa’s early engineering history.

Finally, two watershed events in Lisa’s development were Jobs’ visit to PARC in 1979 (read more about that here), and Rich Page coming to Apple from HP. It was Page who convinced product development to abandon its original plan to build their own custom processor and use Motorola’s 68000 microprocessor for the Lisa instead.

Rich Page (center) at NeXT in 1989. Page worked on the microcode for the HP3000 minicomputers before joining Apple and making the decision to use the Motorola 68000 family of microprocessors for the Apple Lisa and later the Macintosh computer. Later he co-founded NeXT with Jobs and led the hardware engineering team there. See Page’s CHM Oral History here. Photo credit: ©Doug Menuez/Stanford University Libraries

The Motorola 68000 was one of the first widely available processors with a 32-bit instruction set that ran at relatively high speeds at the time, helping to support the new graphical user interface (GUI) of the Lisa.

The Lisa Software Sources and Documentation

For those of you interested in digging deeper, there are some great sources and documentation online. Here are a few:

1. The end of the Apple v. Microsoft copyright lawsuit in 1994 around Windows’ use of GUI elements that were similar to those in Apple’s Lisa and Macintosh operating systems made it possible for Rod Perkins to publish his article on the history of the development of the Lisa user interface in 1997.
2. Transcripts of two talks at CHM by Larry Tesler and Chris Espinosa on that history and the development of the Macintosh can be found here. Or, the video can be watched here.
3. A nice summary of the UI development of Lisa and a mention of connections to HP can be found here.
4. Additional articles on the history of Lisa and primary sources on the source code can be found here.

There are still gaps in the development engineering documents. Hopefully more will be found now that the source code is available for study. A full description of the structure of the code would be much too long for a blog post, but additional research and documentation will appear in the future. For now, have fun digging into the source code and the documentation currently online. Access the code here.

Editor’s note: In addition to recovering the source code for the Lisa computer from diskettes loaned to CHM from Apple, Al Kossow works to restore many of the unique and historic machines in CHM’s extensive collection.

Sign Up!

Learn more about the Art of Code at CHM or sign up for regular emails about upcoming source code releases and related events.

The post Apple Lisa: Still More to Uncover appeared first on CHM.

Today, CHM is often described as the home of the world’s preeminent computer history collection, and many generous donors reach out, hoping the Museum will accept their materials to preserve for posterity.

Once in a while, CHM collections’ staff encounter a desperate situation where exceptional historical materials are in imminent danger of destruction.

This is the story of how a small team of committed museum professionals and concerned employees rescued key records of online history, during a pandemic, in record time.

Background

Back in the 1980s and 90s, before the internet was available to all, ordinary people got online through service providers like CompuServe. With over three million members, CompuServe was a vibrant community complete with social networking, news, e-commerce, personal ads, and email.

Over the years, the company was acquired by other companies. Marc Weber, CHM’s Internet History Program curator and director, often wondered where its records might have gone. Then he got an email from a web history contact offering CompuServe’s official archives intact.

All was on track for the collection to come to CHM, at least until CompuServe got acquired yet again. Dave Eastburn, the archive’s cofounder along with fellow former CompuServe executive Sandy Trevor, confirmed that CHM could still have the archive. But there was a catch. The building it was stored in had to be vacated by Labor Day… only weeks away!

The CompuServe storeroom was huge, chock-full of over 200 boxes worth of documents, brochures, software, and hardware. It contained a veritable treasure trove of all aspects of the early online world, a gold mine for sociologists, historians and business students. But the collection was 2,500 miles from California, Dave was in North Carolina and the Delta variant was everywhere. What to do?

The following is a rough reenactment of what happened.

CompuServe historic software; part of an archive that also included hardware, magazines, CD-ROMs, newsletters, advertisements, membership kids, radio ads, video broadcast commercials and more.

Act I: The Setup

INT. MANY HOME OFFICES – DAY AND NIGHT

CHM COLLECTIONS STAFF sit glued to their computer screens reading email, biting their nails, and tearing their hair between fast and furious typing.

EMAIL DINGS

A ZOOM conference call begins.

COLLECTIONS MANAGER
(worried)
Do we have room for all of it? Do we even know how large it is? What does the collection actually contain?

ARCHIVIST
(embarrassed)
Where is it located again?

REGISTRAR
There’s almost every kind of corporate document, but do we want it all?

CURATOR
Hey, it’s just easier to take it all.

COLLECTIONS MANAGER
But how do we pack and move it? With the pandemic, it’s a shipping and logistics nightmare right now.

DAVE
(enthusiastically)
I can drive to Ohio and while I’m there in the storeroom, I’ll call you on Zoom and show you everything!

ACQUISITIONS REGISTRAR
That’s great! With Dave’s on-site help, and the blessings of remote tech, we can determine in real-time what’s most historically significant and should be saved.

COLLECTIONS MANAGER
So, do we have enough space to house it?

CURATOR
(urgently)
CompuServe is really important. We have to do this!

FADE OUT

This is not the ideal way to transport archival material, but during a global pandemic with supply chain problems it may be the best you can do.

Act II: The Rescue

OHIO STORAGE SITE – DAY

CHM ARCHIVIST working remotely in Michigan during the pandemic finds a brief window of time to buy boxes, packing tape, and Sharpies. She drives three hours to the Ohio site and reviews and packs everything not already boxed for shipping. Two additional helpers are found to help pack on the one day she has to complete this monumental task.

HOME OFFICES – DAY AND NIGHT

REGISTRAR works 24/7 to find a shipper. Not one but two companies commit to the job and then disappear when she tries to confirm details and make a down payment. With COVID and the general supply chain meltdown, this has become an especially challenging task.

BAY AREA ARCHIVIST struggles to make room for up to seven pallets of boxes by shifting materials in CHM’s loading dock/incoming collection’s quarantine area.

CURATOR asks peer institution the Internet Archive if they want the five giant bookshelves full of operations manuals—and they do. With their help the entire archive can be saved!

REGISTRAR struggles to arrange pre-payment for shipping when one truck driver requires half at pick up and another driver gets half at delivery, but neither will take the corporate credit card nor PayPal.

Pickup is the next challenge. Movers don’t show up for a couple of pickup dates. The final chance for pick up is the Friday before the Labor Day deadline. Again, a no show. Will all be lost?

But there is a Plan B. CURATOR had left a deposit with a local moving company to pick up and store the boxes on Monday—just in case. With the help of former CompuServe programmers to identify materials, the local movers take the archive safely to their warehouse.

The interstate shipper finally collects the archive from the local mover’s warehouse. But there’s not enough room for everything on the truck… 60 boxes are left behind in storage!

FADE OUT

The first batch arrives at the CHM Shustek Research Archives after an epic journey. Here’s the rescued collection (boxes on left) in storage quarantine to check for pests.

INT. CHM ARCHIVES – SUNDAY, 7 AM

ARCHIVIST, REGISTRAR, NEW HUSBAND HELPER receive the shipment. They survey the battered and crushed boxes in the truck stacked seven boxes high with dismay.

The driver and local hired help unload the trailer. Staff set up six pallets to hold in collection’s quarantine to check for pests before entering the main building.

ARCHIVIST begins surveying and re-boxing the materials in pristine, new archival boxes.

REGISTRAR looks for a new shipper to move the boxes that remain in Ohio. Finally, they are on their way to the Museum.

Everyone leaves for a much-deserved winter vacation.

FADE OUT

Carefully transferred from damaged moving boxes and re-boxed into museum quality acid free boxes, the collection is now preserved at the Computer History Museum’s Shustek Research Archives.

Act III: The Resolution

INT. CHM ARCHIVES – DECEMBER 22, DAY

COLLECTIONS MANAGER arrives to receive the remaining material. She is relieved to see that the second delivery is perfect; the boxes are well-palletized and stable. The Internet Archive will pick up the operations manuals later for their collection.

Teamwork saves the day! The CompuServe collection has been saved from destruction. All feel immense satisfaction and look forward to cataloging the new collection for the next three years. But wait… a call comes in. Does another collection need to be rescued?

THE END

Stay tuned for the (inevitable) sequel to Mission Impossible: CHM Edition.

SUPPORT CHM’S OWN MISSION (IMPOSSIBLE)!

Blogs like these would not be possible without the generous support of people like you who care deeply about decoding technology. Please consider making a donation.

The post Mission Impossible: CHM Edition appeared first on CHM.

Monday, March 16, 2020, started like any other day at the Museum: staff and volunteers welcomed visitors to our exhibits and behind-the-scenes employees were busy planning the next event, developing content, archiving the collection, or working on museum operations. The executive staff was gathered for a weekly meeting, discussing the potential unfolding impact of COVID-19 when we received notification that Santa Clara County was implementing a “shelter-in-place” directive effective Tuesday, March 17 at 12:01 a.m.

In the midst of change, we found ways to be creative and adapt and, as a result, have become more open than ever! Our new digital front door—our website—has allowed us to reimagine the museum experience, including how we host events, share activities and resources, and provide access to exhibits and tours.

That day the Museum staff made the transition from our place-based office life to working from home. Looking back, the entire effort was a balance of teamwork, community support, new tools at the right time, and most importantly digging deep to find a new level of stamina and creativity.

In normal times, the museum field is very welcoming and supportive. Museum professionals often reach out to each other to share ideas or pick each other’s brains. And during the early days of the pandemic it was no different. Just three days after the shelter-in-place order, Bay Area museum CEOs and directors set-up a weekly zoom call to share information, strategy, and operational plans. Discussions ranged from finances and the Payroll Protection Plan to new digital strategies; how to recoup lost revenue to how to create virtual education or gala events; what to do about summer camps to how to care for and feed the animals in zoos and aquariums. Three things really struck me about these conversations: a deep commitment to mission, a desire to serve audiences no matter what, and a “staff first” mindset as we worked to create a collaborative and supportive virtual work environment. In some ways the weekly group meeting felt like therapy.

Within the CHM community, we  made communication a priority. The executive staff met daily to check in with each other and their teams, which now continues three times a week. The CEO wrote the board of trustees “weekend updates” on Fridays. We implemented virtual all-hands meetings while departments set-up regular check-ins. We launched a popular #athome channel on Slack (a messaging app) so that staff could share their working-from-home highs and lows but generally to make each other laugh.

CHM’s #athome channel on Slack has become the place for sharing recipes, gardening hacks, pets, and more!

The marketing team sent updates to volunteers and members. And,  the development team reached out to museum members, wishing them and their families well and letting them know how the Museum was doing. First and foremost, the health and safety of our staff, volunteers, members, and visitors were our top priority. 

From an operations standpoint, because CHM was deemed a “Nonessential Business,” as defined by the state, most of the staff, volunteers, and contractors have vacated the premises to work from home. A small team continues to work on-site to monitor the safety and security of our building and collections. We are also proactively working through scenarios both short and  longer term to prepare for the pandemic’s effects on the local economy and cultural and business environments. The CHM finance team deserves high praise for securing the Payroll Protection Plan for CHM, allowing staff  to stay employed as long as possible. Unfortunately some Bay Area museums have not fared as well. For all of the local and national museums, the goal has been to preserve staff and uphold mission as long as possible in hopes of weathering the  storm and returning intact and, if possible, even stronger. We sincerely hope to open our doors as soon as it is safe.

It also turned out that our decision to improve the Museum’s digital infrastructure about a year ago really paid off during the current crisis. First, the Museum launched a new website in fall 2019 with significantly improved functionality, allowing us to build and publish digital content more quickly and to re-package our online content for an “at home” audience. 

Check out all of CHM’s virtual activities and resources, perfect for at-home learning. Our resources introduce technological and historical concepts in creative and engaging ways for learners of all ages.

Second, the IT team relocated services like our helpdesk, office drives, collaboration tools, etc. to the cloud,  allowing them to continue to remotely support staff with minimal interruption. We were also in the middle of an institution-wide upgrade of our donor and customer systems service systems to Salesforce. Shelter-in-place gave staff the opportunity to focus on this ambitious project, and staff who normally worked at the front desk and store were able to participate in the migration and quality control. And last but not least, the Museum was fortunate to have received a donation of new laptops from Microsoft. This was big news for the staff, as some of us had been working on 10-year-old laptops. With some long days and careful planning, the IT team configured and delivered laptops in the final hours on our last day at the Museum. It was truly a remarkable morale booster to leave the mothership and face an unknown world with a new laptop, a lifeline to each other. 

And then there is Zoom. The amazing, exhausting platform we are living in day to day. For the Museum, mastering Zoom has become a critical priority in order to engage our audiences through our popular speakers series, CHM Live. Just three weeks after shelter-in-place, we pivoted from in-person events to virtual events—first on April 27 with Microsoft CTO Kevin Scott on the growing digital divide between rural and urban America and then on May 18 with Affectiva CEO Rana el Kaliouby on emotional AI. And while we are still discovering the mysteries of Zoom, our media team is well on its way to Zoom mastery, not just for upcoming events but also for our oral history program. We are shipping pop-up kits complete with a lighting solution (lighting is everything, they say), external microphone, and camera to achieve the highest quality possible given the circumstances. These are all skills that will serve us well in the long run, as they will allow us to collect and tell more stories than ever before. And you can’t beat the endless possibilities of self-expression with those Zoom backgrounds. 

Even though our all-staff meetings and museum happy hours may look a little different, our HR staff has made sure that CHMers still feel a sense of community.

 The education team is also adjusting to the “new normal” and exploring how to reach youth through a digital first strategy. Pilots and prototypes are underway to virtualize our workshops and work with partners with distribution platforms. The team is thinking out of the box (literally) and exploring how to create programs that not only have a positive impact on human lives but also bring a smile on their faces. In March, our team re-organized our website to make accessible activities and resources for our at-home audiences, including a popular virtual tour of Revolution, videos and lesson plans for families and adults as well as a new virtual version of our family-oriented Revolution scavenger hunt, which has been very successful with over 1,500 visits in just four months. 

You might wonder how the collections team, whose daily work is to care for the world’s largest collection of computing artifacts, archives, and historical software, might do their job from home. The answer is one part timing and three parts creativity. The team was in the final months of a federally funded collection processing grant and was able to complete the work by meticulously transporting remaining items home to process while also finalizing finding aids and reports. Much to the group’s surprise they found remote work freeing in terms of thinking through new ways to work together, not unlike moving into a new empty house and experimenting with solutions you never thought possible in the old space. The team is actively exploring new tools like Airtable, a collaboration app that  consolidates multiple spreadsheets and databases in the cloud, and has already used it to put the collections disaster plan into the cloud, create tracking and sorting views for our  1,000+ oral history collection, and respond to research requests more expediently. They’ve even found themselves having fun on CHM’s social media.

CHM’s collection and curatorial teams have found a new way to share our exhibits with everyone via social media, enlisting the help of a very special and on-the-loose host: Shakey the Robot.

Finally the team has put together plans and funding proposals for the Museum’s new initiative OpenCHM, which includes making CHM’s collection more accessible and searchable online by cataloging the collection in innovative ways and expanding the use of digital tools to aid in search, retrieval, and the creation of mini-galleries on the fly. We want to open up the collection to scholars at the intersection of digital technologies and humanities as well as to the public itself to use the collection for research and creative projects. 

I don’t want to paint too rosy a picture because it has been very challenging for everyone. Balancing work and parenting. Worrying about our family nearby or far away that we can’t visit. We are all working longer hours both to get the work done and to reimagine and implement a new kind of museum. We miss our colleagues, our work spaces, our collections, our exhibits, our programs, our visitors, our trustees, and our members.

CHM Staff celebrates the opening of its new Learning Lab in 2019.

We miss all these things we have built together over the course of time. But these cherished spaces, objects, and people are not gone; they are merely in suspended animation. For now we must turn our attention to the digital world and new ways of thinking. It’s an opportunity, really.  And we are embracing it. It’s a mindset shift that is fitting for a museum that explores how technology can shape a better future. And some time, in that beautiful future we are all longing for, we will bring together our physical treasures and our shiny new digital world and be a better museum for it. Special thanks to our hard working staff, dedicated volunteers and trustees, museum colleagues and members and donors and those we have lost. Thank you all for your camaraderie and support. 

Virtual CHM Live Events

Reprogramming The American Dream with Microsoft CTO Kevin Scott

Girl Decoded: Rana el Kaliouby in Conversation with NPR Contributor Aarti Shahani

Maintenance and invention: Lessons from Hubble with Kathryn Sullivan

Check for Upcoming Events

Missed an event? Check out our CHM Live recaps.

Activities and Resources

• Revolution Virtual Scavenger Hunt, Grades 6–12
• Virtual Tour of Revolution
• Design the Future: For Families in the Classroom

View All Activities and Resources

The post Thriving in Place: CHM’s Journey through the Early Days of the COVID-19 Pandemic appeared first on CHM.

Pamela McCorduck may be one of the few people qualified to make a prediction about where the development of artificial intelligence will lead. But, as a true humanist, she avoids an invitation to hubris. Instead, in the excerpt below from the end of her 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia, she reminds us that humans have always quested into the unknown, that it’s part of being human. She says, “The search for AI parallels our innate wish to fly, to roam over and beneath the seas, to see beyond our natural eyesight. The quest takes us out of the commonplace, along a dark and perilous way, beset with tasks and trials, a collective hero’s journey that all humans must undertake.”

When it comes to the future of AI, McCorduck does not have answers, only questions. Perhaps her principled refusal to land on either the side of salvation or destruction, and to maintain a clear view and an open mind, is a reminder of what the best of human intelligence has to offer.

We can’t now say what living beside other, in some ways superior, intelligences will mean to us. Will it widen and raise our own individual and collective intelligence? In significant ways, it already has. Find solutions to problems we could never solve? Probably. Find solutions to problems we lack the wit even to propose? Maybe. Cause problems? Surely. AI has already shattered some of our fondest myths about ourselves and has shone unwelcome light on others. This will continue.

The future. It’s been easy to resist writing breathless scenarios. Nothing ages faster nor makes the prophet seem so time-bound. As Jack Ma, the co-founder of the Chinese online service, AliBaba says, “There are no experts for the future. Only experts for yesterday.”

When people ask me my greatest worry about AI, I say: what we aren’t smart enough even to imagine.

You might also recognize in all this ferment the two customary opposing views about AI—a catastrophe or a welcome blessing—an early theme from my own “Machines Who Think”: what I’ve called the Hebraic and the Hellenistic views of intelligence outside the human cranium. The Hebraic tradition is encoded in the Second Commandment: “You shall not make for yourself a graven image, or any likeness of any thing that is in heaven above, or that is on the earth beneath, or that is in the water under the earth.”¹ We fear entertaining god-like aspirations, of calling down divine wrath for our overweening, illicit ambition. The Hellenistic view, on the contrary, welcomes (with cheer and optimism) outside help, the creations of our own hands—not that the dwellers in Olympus and their progeny didn’t have problems.²

We already have a bitter taste of the dark side of AI. Russian bots and other software simulated human influencers and interfered with the U.S. national elections in 2016; our telecommunications and social media apps know our lives in granular, even embarrassing detail. The Chinese government, along with the Chinese army, runs deep learning algorithms over the search engine data collected about the users of Baidu, the Chinese equivalent of Google. Every Chinese citizen receives a Citizen Score, to determine whether they can get loans, jobs, or travel abroad (Helbing et al., 2017).³ China is selling these systems to other countries. With all of us under surveillance, whether by our government or by firms, whether by manipulative individuals or scheming terrorists, how the economy and society are organized must change fundamentally. Kai-Fu Lee says we need to rewrite the social contract (2018). We do. Certainly we need to talk.

Let us talk too about the grand ideas in the Western tradition. What is thought? What is memory? What is self? What is beauty? What is love? What are ethics? Answers to these questions have up to now been assertions or hand-waving. With AI, the questions must be specified precisely, realized in executable computer code. Thus eternal questions are being examined and tested anew.

From the beginning, pioneering researchers in the field expected the machines would eventually be smarter than humans (whatever that meant), but they saw this as a great benefit. More intelligence was like more virtue. These early researchers were firmly in the Hellenistic tradition. They believed—and I do too, if you haven’t guessed—that if we’re lucky and diligent, we can create a civilization bright with the best of human qualities: enhanced intelligence, which is wisdom; with dignity, compassion, generosity, abundance for all, creativity, and joy, an opportunity for a great synthesis of the humanities and the sciences, by the people who specialize in each. Herb Simon liked to say that we aren’t spectators of the future; we create it. A better culture, generously life-centered, ethically based yet accommodating infinite human variety, is a synthesizing project worthy of the best minds, human and machine.

We long to save ourselves as a species. For all the imaginary deities throughout history who’ve failed to save and protect us from nature, from each other, from ourselves, we’re finally ready to substitute the work of our own enhanced, augmented minds. Some worry it will all end in catastrophe. “We are as gods,” Stewart Brand famously said, “and might as well get good at it (1968).” We’re trying. We could fail.

Win or lose, we’re impelled to pursue this altogether human quest. Some mysterious but profound yearning has led us here from the beginning. This is the deep truth of our legends, our myths, our stories. (It wants some explanation. This isn’t exactly the joy of sex.) The search for AI parallels our innate wish to fly, to roam over and beneath the seas, to see beyond our natural eyesight. The quest takes us out of the commonplace, along a dark and perilous way, beset with tasks and trials, a collective hero’s journey that all humans must undertake.

The tasks and trials we already see include the destruction of whole business models, the transformation of work (and thus for many, life’s meaning), and faster-than-thought applications with unforeseen consequences. We face a possible, if unlikely, subjugation to the machines; a possible, if unlikely, destruction of the human race by AI. These seem to me remote, but trials we can’t yet foresee will surely emerge. We hardly know how to meet the trials we can see. I quoted Herb Simon above: “We aren’t spectators of the future; we create it.” But often he also slightly misquoted Proverbs: “If the leaders have no vision, the people will perish.”

For years I had these calligraphed words framed above my desk, a gift from my husband: “And wherefore was it glorious?”

I knew the rest of the passage by heart:

Not because the way was smooth and placid as a southern sea, but because it was full of dangers and terror, because at every new incident your fortitude was to be called forth and your courage exhibited, because danger and death surrounded it, and these you were to brave and overcome. For this was it a glorious, for this was it an honourable undertaking. You were hereafter to be hailed as the benefactors of your species, your names adored as belonging to brave men who encountered death for honour and the benefit of mankind.

These are the words of the dying Dr. Victor Frankenstein, near the end of Mary Shelley’s essential novel, “Frankenstein.” He cries out to a ship’s crew that, during a hunt for the Northwest Passage, has been paralyzed with terror by the menacing ice. Yes, the words reflect ironically on his repudiation of his own creation of an extra-human intelligence. The deeper urgency, I believe, is his, and our, struggle to be brave, as we go where we must.

Notes

1. From Exodus 20:4, King James Version.
2. The same division is evident in biological enhancement of human faculties. Some fear this very much; others think it would be a benefit. The combination of much smarter humans and much smarter machines is something to think about.
3. Helbing, et al. should certainly be one of the texts we talk about.

More from This Series

• AI Is Already Here, For Good Or Bad
• The Promise of the Doctor Program: Early AI At Stanford
• Panic and Privilege

About “This Could Be Important”

Pamela McCorduck was present at the creation. As a student working her way through college at Berkeley, she was pulled into a project to type a textbook manuscript for two faculty members in 1960, shortly before she was set to graduate. The authors, Edward Feigenbaum and Julian Feldman, happened to be two of the founding fathers of artificial intelligence. For McCorduck, it was the start of a life-long quest to understand—and document for the rest of us—the key players, underlying ideas, and critical breakthroughs in this transformative technology. 

Part memoir, part social history, and part biography, McCorduck’s 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia, shares both personal anecdotes of the giants of AI and insightful observations from the perspective of a humanities scholar. Brought to readers by Carnegie Mellon University Press, CHM is thrilled to provide a series of four telling excerpts from the book.

About Pamela McCorduck

Pamela McCorduck is the author of eleven published books, four of them novels, seven of them non-fiction, mainly about aspects of artificial intelligence. She lived for forty years in New York City until family called her back to California where she now lives in the San Francisco Bay Area.

The post The Future: Humans and AI appeared first on CHM.

Science and technology and traditional “humanities” topics such as language, government, ethics, and writing, influence and inform our daily lives. We’re often unaware of how they intersect, although our educational system places a clear dividing line between the two different “cultures”: the hard sciences and the humanities. A literature scholar and novelist, Pamela McCorduck transcends those conceptual boundaries and turns a critical eye on the divide. In her 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia, McCorduck relates how she’s seen the two cultures converge in the field of artificial intelligence. Humanists and computer scientists alike ask questions about what exactly “intelligence” is and what it means to be human. 

In the excerpt below, McCorduck explores how privileged white males’ dominance of Western culture is challenged by the idea of an artificial intelligence. Unlike women and people in less powerful positions, they aren’t used to having their worldview unconsidered, undervalued, or superseded. Interestingly, McCorduck notes that IBM’s Watson is characterized as a “he.” We should all be wary of attributing a male gender to a new type of non-human intelligence with potentially superior abilities lest we perpetuate existing stereotypes and harmful power dynamics. 

We must also apply a humanistic lens to the ongoing development of AI and machine learning, thinking deeply about incorporating in them “the FATES”: fairness, accountability, transparency, ethics, security, and safety. If we don’t, the “autonomous revolution” of AI could indeed lead to the dystopian world decried by threatened white males. But if we do, it just might bring a new kind of utopia, one with equal promise for all human beings.

In the mid-teens of the 21st century, a startling efflorescence appeared of declarations, books, articles, and reviews. (Typical titles: “The Robots Are Winning!” “Killer Robots are Next!” “AI Means Calling Up the Demons!” “Artificial Intelligence: Homo sapiens will be split into a handful of gods and the rest of us.”) Even Henry Kissinger (2018) tottered out of the twilight of his life to declare that AI was the end of the Enlightenment, a declaration to give pause for many reasons.

The profound, imminent threat AI made to privileged white men caused this pyrexia. I laughed to friends, “These guys have always been the smartest one on the block. They really feel threatened by something that might be smarter.” Because most of these privileged white men admitted AI had done good things for them (and none of them so far as I know was willing to give up his smartphone), they brought to mind St. Augustine: “Make me chaste, oh Lord, but not yet.”

Very few women took this up the same way (you’d think we don’t worry our pretty heads). One who did, Louise Aronson, a specialist in geriatric medicine (2014), dared to suggest that robot caregivers for the elderly might be a positive thing, but Sherry Turkle (2014), another woman who responded to Aronson’s opinion piece in The New York Times with a letter to the editor, worried that such caregivers only simulated caring about us. That opened some interesting questions about authentic caring and its simulation even among humans, but didn’t address the issues around who would do this caregiving and how many of those caregivers society could afford.

As I read this flow of heated declarations about the evils of AI, ranging from the thoughtful to the personally revealing to the pitifully derivative—a Dionysian eruption if ever there was one—I remembered the brilliant concept, described and named by the film critic, Laura Mulvey, in 1975: the male gaze. She coined it to describe the dominant mode of filmmaking: a narrative inevitably told from a male point of view, with female characters as bearers, not makers, of meaning. Male filmmakers address male viewers, she argued, soothing their anxieties by keeping the females, so potent with threat, as passive and obedient objects of male desire. (The detailed psychoanalytic reasoning in her article you must read for yourself.)

In many sentences of Mulvey’s essay, I could easily substitute AI for women: AI signifies something other than (white or Asian) male intelligence and must be confined to its place as a bearer not a maker of meaning. To the male gaze, AI is object; its possible emergence as autonomous subject, capable of agency, is frightening and must be prevented, because its autonomy threatens male omnipotence, male control (at least those males who fret in popular journals and make movies). Maybe that younger me who hoped AI might finally demolish universal assumptions of male intellectual superiority was on to something.

The much older me knows that if AI poses future problems (how could it not?) it already improves and enhances human intellectual efforts and has the potential to lift the burden of petty, meaningless, often backbreaking work from humankind. Who does a disproportionate share of that petty, meaningless, backbreaking work? Let a hundred Roombas bloom.¹

But the handwringing said that people were at last taking AI seriously.

Another great change I’ve seen is the shift of science from the intellectual perimeters of my culture to its center. (Imagine C. P. Snow presenting his Two Cultures manifesto now. Laughable.) These days, not to know science at some genuine level is to forfeit your claims to the life of the mind. That shift hasn’t displaced the importance of the humanities. As we saw with the digital humanities—sometimes tentative, sometimes ungainly, the modest start of something profound—the Two Cultures are reconciling, recognizing each other as two parts of a larger whole, which is what it means to be human. Not enough people yet know that a symbol-manipulating computer could be a welcome assistant to thinking, whether about theoretical physics or getting through the day.

AI isn’t just for science and engineering, as in the beginning, but reshapes, enlarges, and eases many tasks. IBM’s Watson, for instance, stands ready to help in dozens of ways, including artistic creativity: the program (“he” in the words of both his presenter and the audience) was a big hit at the 2015 Tribeca Film Festival when it was offered as eager colleague to filmmakers (Morais, 2015).

At the same time, AI also complicates many tasks. If an autonomous car requires millions of lines of code to operate, who can detect when a segment goes rogue? Mary Shaw, the Alan J. Perlis professor of computer science and a highly-honored software expert, worries that autonomous vehicles are moving too quickly from expert assistants beside the wheel and responsible for oversight, to ordinary human drivers responsible for oversight, to full automation without oversight. She argues that we lack enough experience to make this leap. Society would be better served by semi-autonomous systems that keep the vehicle in its lane, observe the speed limit, and stay parked when the driver is drunk. A woman pushing a bike, its handles draped with shopping bags, was killed by an autonomous vehicle because who anticipated that? If software engineering becomes too difficult for humans, and algorithms are instead written by other algorithms, then what? (Smith, 2018). Who gets warned when systems “learn” but that learning takes them to places that are harmful to humans? What programming team can anticipate every situation an autonomous car (or medical system, or trading system, or. . .) might encounter? “Machine learning is inscrutable,” Harvard’s James Mickens says (USENIX, 2018). What happens when you connect inscrutability to important real-life things, or even what he calls “the Internet of hate” also known as simply the Internet? What about AI mission creep?²

Columbia University’s Jeanette Wing has given thought to these issues and offers an acronym: FATES. It stands for all the aspects that must be incorporated into AI, machine learning in particular: Fairness, Accountability, Transparency, Ethics, Security, and Safety. Those aspects should be part of every data scientist’s training from day one, she says, and at all levels of activity: collection, analysis, and decision-making models. Big data is already transforming all fields, professions, and sectors of human activity, so everyone must adhere to FATES from the beginning.

But fairness? In real life, multiple definitions exist.

Accountability? Who’s responsible is an open question at present, but policy needs to be set, compliance must be monitored, and violations exposed, fixed, and if necessary, fined.

Transparency? Assurances of why the output can be trusted are vital, but we already don’t fully understand how some of the technology works. That’s an active area of research.

Ethics? Sometimes a problem has no “right” answer, even when the ambiguity might be encoded. Microsoft has the equivalent of an institutional review board (IRB) to oversee research (Google’s first IRB fell apart publicly after a week), but firms aren’t required to have such watchdogs, nor comply with them. According to Wing, a testing algorithm for deep learning, DeepXplore, recently found thousands of errors, some of them fatal, in fifteen state-of-the-art data neural networks in ImageNet and in software for self-driving cars. Issues around causality versus correlation have hardly begun to be explored.

Safety and security? Research in these areas is very active, but not yet definitive.

This could be important.

So I said again and again over my lifetime. Now we know. AI applications arrive steadily. Some believe we’ll eventually have indefatigable, smart, and sensitive personal assistants to transform and enhance our work, our play, our lives. Researchers are acting on those beliefs to bring such personal assistants about: the Guardian Angel, Maslow, Watson. With such help, humans could move into an era of unprecedented abundance and leisure. Others cry halt! Jobs are ending! Firms and governments are spying on our every move! The machines will take over! They want our lunch! They lack human values! It will be awful!³

Which will it be?

Notes

1. Journalist Sarah Todd wrote “Inside the surprisingly sexist world of artificial intelligence” (Quartz, October 25, 2015) about the sexism and lack of diversity in AI. The piece suggests women won’t pursue AI because it de-emphasizes humanistic goals. Maybe public fears about the field are because of the homogeneity of the field, she went on. To close the gap, schools need to emphasize the humanistic applications of AI. And so on. Although many applications of AI grow out of a sexist culture and reflect that, readers of this history can also see the fallacies in Todd’s argument. AI started out as a way of understanding human intelligence. That continues to be one of its major goals, which is why it partners with psychology and brain science. Its humanistic goals are central, whether to understand intelligence or to augment it. But all scientific and technological fields save, perhaps, the biological sciences, could use more women practitioners and more people of color. That is being addressed in many places and many ways, beyond the scope of this book, but one example is the national nonprofit AI4All, launched in 2017 by Stanford’s Fei-Fei Li and funded by Melinda Gates, which aims to make AI researchers, hence AI research, more diverse. The 2019 report from NYU says this is not enough (West et al., 2019).
2. The video in which Mickens’ quote appears is mostly about the perils of machine learning, especially the hilariously sad story of Tay, Microsoft’s chatbot, which had to be taken down from the Internet after 16 hours because of what it was learning from its training set, the gutter of the Internet.
3. The cries of pain and alarm are too numerous to list. Privacy, meddling, reshaping our sense of ourselves as unique, and more. About the future job market, for example, books and articles abound. See, for example, the relatively optimistic book by Erik Brynjolfsson and Andrew McAfee, Race Against the Machine: How the Digital Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy (Ditigal Frontier Press, 2011) or the careful quantitative study from the University of Oxford by Carl Benedikt Frey and Michael A. Osborne, “The Future of Employment: How Susceptible are Jobs to Computerisation?” (September 17, 2013 and available via https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf). But later economists question these findings as mere extrapolation, with no allowance for new jobs that will be created. For example, Forbes.com’s Parmy Olson wrote about a PwC report on AI in “AI won’t kill the job market but keep it steady, PwC report says” (July 17, 2018).

Look for the final excerpt from This Could Be Important on April 22.

More from This Series

• AI Is Already Here, For Good Or Bad
• The Promise of the Doctor Program: Early AI At Stanford
• The Future: AI and Humans

About “This Could Be Important”

Pamela McCorduck was present at the creation. As a student working her way through college at Berkeley, she was pulled into a project to type a textbook manuscript for two faculty members in 1960, shortly before she was set to graduate. The authors, Edward Feigenbaum and Julian Feldman, happened to be two of the founding fathers of artificial intelligence. For McCorduck, it was the start of a life-long quest to understand—and document for the rest of us—the key players, underlying ideas, and critical breakthroughs in this transformative technology. 

Part memoir, part social history, and part biography, McCorduck’s 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia, shares both personal anecdotes of the giants of AI and insightful observations from the perspective of a humanities scholar. Brought to readers by Carnegie Mellon University Press, CHM is thrilled to provide a series of four telling excerpts from the book.

About Pamela McCorduck

Pamela McCorduck is the author of eleven published books, four of them novels, seven of them non-fiction, mainly about aspects of artificial intelligence. She lived for forty years in New York City until family called her back to California where she now lives in the San Francisco Bay Area.

The post Panic and Privilege appeared first on CHM.

Pamela McCorduck was AI pioneer Ed Feigenbaum’s assistant in 1965 when she had an epiphany that changed her life. World-famous Russian computer scientist Andrei Yershov visited Stanford and wanted to see the Doctor program, one of the earliest interactive computer programs. In her 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia, McCorduck describes what happened when Yershov sat down in front of the teletype machine that would allow him to communicate with the computer by text. 

Yershov responded to the computer’s opening pleasantries by writing that he was tired from traveling and being away from home. The computer wrote back: “Tell me about your family.” While McCorduck and others watched, Yershov confided to the machine his intimate worries about his wife and children. Witnessing how the Doctor program evoked such an emotional response from a computer scientist even though he knew it was just a machine, McCorduck realized that something important was happening: there had been a connection between two minds, one human and one artificial.

In the excerpt below, McCorduck describes how the early Doctor program illustrates many issues that still surround artificial intelligence. There’s the dream of harnessing AI for a better future, concerns about ethics at the intersection of AI and human behavior, and the clash of personalities and perspectives in a new field with both unprecedented power and unknown risk. 

Today, medical chatbots, descendants of the Doctor program, are used to monitor patients, answer questions, and coach people to take their medications. Research has shown that people even reveal more about their health conditions, and their lapses in following doctors’ orders, to computers than they do to the doctors themselves because they don’t feel judged. McCorduck takes us back to the past where the future began.

At Stanford, I was learning by osmosis again, the way I’d learned from the graduate students at Berkeley. I was mainly learning about AI, deeply important at Stanford, which, along with Carnegie Mellon and MIT, was then one of the three great world centers of AI research. All three were undisputed world centers of computing research generally, and it’s no coincidence that AI was centrally embedded in that wider, pioneering research.

Ed Feigenbaum had come to Stanford hoping that he and John McCarthy could collaborate. They remained personally friendly but realized their destiny was to pursue different paths in AI research. When I arrived at Stanford, McCarthy was in the process of moving his research team to a handsome, low-slung semicircle of a new industrial building in the Stanford hills, perhaps five miles from Polya Hall. A now defunct firm called General Telephone and Electric, seeing the new structure didn’t fit their research plans after all, had given it to Stanford, and it became the Stanford Artificial Intelligence Laboratory, SAIL.¹

Among the research projects that had moved from Polya Hall to SAIL was Kenneth Colby’s Doctor program. Colby was an MD and psychiatrist who thought there must be some way to improve the therapeutic process—perhaps by automating it. Patients in state psychiatric hospitals might see a therapist maybe once a month if they were lucky. If instead they could interact with an artificial therapist anytime they wanted, then whatever its drawbacks, Colby argued, it was better than the current situation. In those prepsychotropic drug days, Colby wasn’t alone in thinking so. Similar work was underway at Massachusetts General Hospital. Colby had collaborated for a while with Joseph Weizenbaum, an experienced programmer, who’d come from a major role in automating the Bank of America and was interested in experimenting with Lisp. Weizenbaum would soon create a dialect of Lisp called Slip, for Symbolic Lisp, though it really had no symbolic aspirations as AI understood the term.

Doctor was the program that the visiting and eminent Soviet scientist, Andrei Yershov, asked to see. His encounter with Doctor was the moment that artificial intelligence suddenly became something deeper and richer for me than just an interesting, even amusing, abstraction.

But Doctor raised questions. Should the machine take on this therapeutic role, even if the alternative was no help at all? The question and those that flowed from it deserved to be taken seriously. Arguments for and against were fierce. Weizenbaum warned that the therapeutic transaction was one area where a machine must not intrude, but Colby said machine-based therapy was surely preferable to no help at all.

Thus Doctor was the beginning of a bitter academic feud between Weizenbaum and Colby, which I would later be drawn into when I published “Machines Who Think” and made for myself a determined enemy in Weizenbaum.

At the time Yershov was playing (or not) with the Doctor demonstration, Weizenbaum was already beginning to claim that Colby had ripped him off—Doctor, he charged, was just a version of Weizenbaum’s own question-answering program, called Eliza (after Eliza Doolittle). Eliza was meant to simulate, or caricature, a Rogerian therapist, which simply turned any patient’s statement into a question. I’m feeling sad today. Why are you feeling sad today? I don’t know exactly. You don’t know exactly? Feigenbaum, who’d taught Lisp to Weizenbaum, says that Eliza had no AI aspirations and was no more than a programming experiment.

Colby objected strenuously to Weizenbaum’s charges. Yes, they’d collaborated for a brief period, but putting real, if primitive, psychiatric skills into Doctor was Colby’s original contribution and justified the new name. Furthermore, Colby was trying to make this a practical venture whereas Weizenbaum had made no improvements in his toy program.

Maybe because Weizenbaum seemed to get no traction with his claims of being ripped off, he turned to moralizing. Even if Colby could make it work, Doctor was a repulsive idea, Weizenbaum said. Humans, not machines, should be listening to the troubles of other humans. That, Colby argued, was exactly his point. Nobody was available to listen to people in mental anguish. Should they therefore be left in anguish?²

I agreed with Colby. Before this, I might not, and based only on first feelings, have sided with Weizenbaum.

But at Stanford, I was learning to think differently. One day, I tried to explain to Feigenbaum how I’d always groped my way fuzzily, instinctively into issues, relying on feelings. Now I began to think them through logically. Ed laughed. “Welcome to analytic thinking.”

I’d entered university hoping to learn “the best which has been thought and said in the world,” as I read in Matthew Arnold’s “Culture and Anarchy” in my eager freshman year. But Arnold said more: the purpose of that knowledge was to turn a stream of fresh and free thought upon our stock notions and habits.

For me, meeting artificial intelligence did exactly that.

Notes

1. Read an autobiography of SAIL at http://infolab.stanford.edu/pub/voy/museum/pictures/AIlab/SailFarewell.html
2. By 2018, online therapy was thriving. One project, a joint effort between Stanford psychologists and computer scientists, and called Woebot, offered cheap but not free therapy to combat depression. It was a hybrid—one part interaction with a computer, and one part interaction with human therapists, this for people who couldn’t afford the high cost of conventional therapy. Earlier projects included one at the Institute for Creative Technologies in Los Angeles, called Ellie, to assist former soldiers with PTSD. Ellie’s elaborate protocols seem to have overcome the problem that many patients resist telling the truth to a human therapist but feel freer with a computer. (We saw this with Soviet computer scientist Andrei Yershov.) Some decades ago, the Kaiser Foundation discovered the same reaction to ordinary medical questions—people felt judged by human doctors in ways they didn’t by computers and could thus be more candid. 

Look for the next excerpt from This Could Be Important on April 8.

More from This Series

• AI Is Already Here, For Good Or Bad
• Panic and Privilege
• The Future: AI and Humans

About “This Could Be Important”

Pamela McCorduck was present at the creation. As a student working her way through college at Berkeley, she was pulled into a project to type a textbook manuscript for two faculty members in 1960, shortly before she was set to graduate. The authors, Edward Feigenbaum and Julian Feldman, happened to be two of the founding fathers of artificial intelligence. For McCorduck, it was the start of a life-long quest to understand—and document for the rest of us—the key players, underlying ideas, and critical breakthroughs in this transformative technology. 

Part memoir, part social history, and part biography, McCorduck’s 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia, shares both personal anecdotes of the giants of AI and insightful observations from the perspective of a humanities scholar. Brought to readers by Carnegie Mellon University Press, CHM is thrilled to provide a series of four telling excerpts from the book.

About Pamela McCorduck

Pamela McCorduck is the author of eleven published books, four of them novels, seven of them non-fiction, mainly about aspects of artificial intelligence. She lived for forty years in New York City until family called her back to California where she now lives in the San Francisco Bay Area.

The post The Promise of the Doctor Program: Early AI At Stanford appeared first on CHM.

“AI is us,” writes Pamela McCorduck in her 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia. From the smartphone in your pocket to the car that helps you park and the robot that cleans your floors, we’ve assimilated AI into our lives. But many of us still fear that the machines will “take over” and find the idea of non-human intelligence deeply disturbing. Steeped in the history of AI, McCorduck understands those concerns and the very real dangers inherent in AI in terms of security and privacy and algorithms that reflect their creators’ bias, but she remains optimistic. 

In the excerpt below, McCorduck explores the promise and perils of AI and robots as new forms of intelligence that will be even smarter than humans. This doesn’t have to be scary. Since the dawn of AI, humans’ understanding of the intelligence of other living things has expanded to include “primates, cetaceans, elephants, dogs, cats, racoons, parrots, rodents, bumblebees, and even slime molds.” There are trees that send chemical warnings to each other when beetles attack, arguably a form of intelligence. “Entire books appear on comparative intelligence across species, trying to tease out what’s uniquely human. It isn’t obvious,” McCorduck writes.

How should we consider our new understanding of entities other than humans that appear intelligent? Isn’t it possible our knowledge has made us ever more aware of and concerned about protecting our fellow creatures and the environment we all share? And so, why wouldn’t an exponentially smarter artificial intelligence make better decisions for our welfare than those we are capable of making ourselves?

It will ask questions we don’t even know how to ask. It will think the things we are incapable of thinking. It will experience and feel the things that we aren’t capable of. Yes, I believe that will happen eventually. We think of AI in terms of personal gadgets—my search engine will be better, my car will drive itself, my doctor will be better able to heal me, my grandma can be safely left home alone as she ages, a robot will finally do the housework. But greater contributions of AI will be planetary, teasing out how the environment and human wellbeing are subtly intertwined. Al’s greatest contribution might be its fundamental role in understanding and illuminating the laws of intelligence, wherever it manifests itself, in organisms or machines.

 For a long time, I’ve been comfortable with such ideas. Unduly optimistic, maybe, but I look forward to having other, smarter minds around. (I’ve always had such minds around in the form of other humans.) I don’t much worry they’ll want my niche—though that presupposes a planet that won’t, in one of Bostrom’s scenarios, be tiled over entirely with solar panels to supply power for the reigning AI. Humans will endure, but possibly not as the dominant species. Instead, that position might belong someday to our non-biological descendants. But really, the scary future scenarios sound as if humans have no agency here. We certainly do, and as we’ll see, it’s already at work.

A search (powered by AI techniques, of course) will quickly show how we’ve already woven AI around and inside our lives, turning scientific inquiry into human desire, even stark necessity. When we did not—the nuclear catastrophe of Fukushima Daiichi, for example—we wished we had. AIs fly, crawl, inhabit our personal devices, connect us with each other willingly or not, shape our entertainment, and vacuum the living room.

Robots, a particularly visible form of AI (embodied, in the field’s term), occupy a significant space in our imaginations, their very birthplace. Books, movies, TV, and video games provoke us to conjecture about some of the ways we might behave and the issues embodied AIs will raise when they become our companions. But this visible embodiment, humanoid or otherwise, is only one form AIs will take. The disembodied, more abstract intelligences, like Google Brain, AlphaZero, and Nell¹ at Carnegie Mellon are hidden inside machines invisible to the human eye, scoffing at human boundaries. Their implications are even more profound.

Distributed intelligence and multiagent software inhabit electronic systems all over the globe, seizing information that can be studied, analyzed, manipulated, redistributed, re-presented, exploited, above all, learned from. Human knowledge and decision-making are rapidly moving from books and craniums into executable computer code. But fair warnings and deep fears abound: algorithms that take big data at face value reinforce the bigotries those data already represent. Bad enough that data about you you’re aware you’re volunteering (submitted for drivers’ licenses for example) are collected, aggregated, and marketed; much worse that involuntary data collected from your on-line behavior (your purchases, your use of public transportation) is also a profit center and a spy on you. Horrors have crawled up from the dark side: bots that lie and mislead across social media, trolls without conscience, and applications whose unforeseeable consequences could be catastrophic.

Larry Smarr, founding director of the California Institute for Telecommunications and Information Technology, on the campus of the University of California at San Diego, calls this distributed intelligence and multiagent software the equivalent of a global computer. “People just do not understand how different a global AI will be with all the data about all the people being fed in real time,” he emailed me a few years ago. By sharing data, he continued, the whole world is helping to create AI at top speed, instead of a few Lisp programmers working at it piecemeal. The next years will see profound changes. In short, AI already surrounds us. Is us.

The industrialization of reading, understanding, and question-answering is well underway to be delivered to your personal device. Some of these machines learn statistically; others learn at multiple, asynchronous levels, which resembles human learning. They don’t wait around for programmers but are teaching themselves. Understanding the importance of this, many conventional firms like Toyota or General Electric are reinventing themselves as software firms with AI prominent.

Word- and text-understanding programs particularly interest me, partly because I’m a word and text person myself, and partly because words, spoken or written, at the level of complexity humans do them, seem to be one of the few faculties that separate human intelligence from the intelligence of other animals. (Making images is another.) Other animals communicate with each other, of course. But if their communication is deeply symbolic, that symbolism has so far evaded us. Moreover, humans have means to communicate not only face to face, but also across generations and distances, and we do so orally, then by pictorial representations, by speaking, creating pictures, writing, print, and now by electronic texts and videos.

For a long time, we were the only symbol-manipulating creatures on the planet. Now, with smarter and smarter computers, we at last have symbol-manipulating companions. A great conversation has begun that won’t be completed for a long time to come.

Notes

1. In this book, I will not capitalize most program acronyms or abbreviations, except for initial caps. It’s unnecessary and tiring to the reader’s eye.

Look for the next excerpt from This Could Be Important on March 25.

MORE FROM THIS SERIES

• The Promise of the Doctor Program: Early AI At Stanford
• Panic and Privilege
• The Future: AI and Humans

About “This Could Be Important”

Pamela McCorduck was present at the creation. As a student working her way through college at Berkeley, she was pulled into a project to type a textbook manuscript for two faculty members in 1960, shortly before she was set to graduate. The authors, Edward Feigenbaum and Julian Feldman, happened to be two of the founding fathers of artificial intelligence. For McCorduck, it was the start of a life-long quest to understand—and document for the rest of us—the key players, underlying ideas, and critical breakthroughs in this transformative technology. 

Part memoir, part social history, and part biography, McCorduck’s 2019 book, This Could Be Important: My Life and Times with the Artificial Intelligentsia, shares both personal anecdotes of the giants of AI and insightful observations from the perspective of a humanities scholar. Brought to readers by Carnegie Mellon University Press, CHM is thrilled to provide a series of four telling excerpts from the book.

About Pamela McCorduck

Pamela McCorduck is the author of eleven published books, four of them novels, seven of them non-fiction, mainly about aspects of artificial intelligence. She lived for forty years in New York City until family called her back to California where she now lives in the San Francisco Bay Area.

The post AI Is Already Here, For Good Or Bad appeared first on CHM.

Software Curator Al Kossow in the Shustek Center’s Bernard L. Peuto Software Laboratory.

The innovations of computing past can offer fresh perspective and provide inspiration to a new generation of innovators. The Software History Center at the Computer History Museum (CHM) is restoring two Xerox Alto computers, part of the center’s Alto System Project. The Alto, introduced in 1973 and created by the Xerox Palo Alto Research Center (PARC), combined features that were rare at the time, including page-oriented displays, a mouse, networking, and interchangeable magnetic disk storage packs for individual user data. The Alto was the first computer that allowed people to focus on using the computer as a tool to accomplish a task rather than on learning their computer’s technical details. Today’s computers and connected devices are direct descendants of some of Alto’s early innovations. More on the revolutionary Alto computer can be found in our permanent exhibition, Revolution: The First 2000 Years of Computing.

The following conversation took place on May 10 between Software Curator and restorer Al Kossow and Director of Digital Collections Paula Jabloner. The conversation provides an in-depth window into the triumphs, challenges, and the work required to restore historical computers. Learn more about the Alto System Project in our 2017 issue of Core magazine.

Paula Jabloner: When were these Altos built?

Al Kossow: Late 1970s.

Paula: What do you think is the most important reason to restore the Altos?

A restored screen and keyboard showing a Pac-Man program. The screen measures 8 ½ x 11 inches.

Al: To be able to shoot video of them. There are some characteristics of the machines that are unique. Like the way the screen looks that is difficult to duplicate in emulation.

Paula: Is that the orientation and size of the screen?

Al: Yes and the kind of phosphor they used. It’s a long persistence phosphor. The screen has a kind of unique way it looks, which isn’t really common. The current emulations actually run at the real speed of the machine. So you get a feel of how fast the machines were even in the emulations.

Paula: But not the look and feel of them?

Al: So you notice when the machine is running you can hear the disk seeking. There are all these noises associated with it when it is actually running that are kind of unique.

Paula: Many of the creators are still around. Is this a unique opportunity, to be able to interview and speak with them about the Alto’s development?

Al: Yeah. There are some things where there is not much documentation. Like Larry Tesler’s Gypsy document program. We have copies of Gypsy that can run. It would be really nice to have Larry demonstrate it. There are other things as well that it would be really great to have the creators being able demonstrate it and explain their thought process.

Paula: The way I interact with my computer is second nature. But, that is, to a large degree, because the Alto innovators conceived of many of these intuitive features over 40+ years ago.

Al: Right. At the time the creators were really thinking very differently. I’ve only been able to use the Ethernet on the machines in the last couple of weeks. The amount of interesting things that they did with networking between the computers is really interesting. So up to this point, I’d been mostly using it as a standalone computer, but there are all these things you can do with it like electronic mail, chat, and things like that once you have connectivity, that are really interesting. And they had all of this stuff working in the late [19]70s. So one of the things that came up when [Steve] Jobs got a demo of this, he commented [that] the one thing he missed or overlooked when he got the demo was the networking. I’m not sure if that was because there was only one machine running and he didn’t realize how well connected these things were but I think it was that the windows and mice and all of that he could immediately see a use for.

An open CRT case. Al estimates an additional month to clean and read the Museum’s disk pack collection. This doesn’t include cataloging and other activities to make the software accessible to others.

Paula: He was so intrigued with the windows and mice, he didn’t even have a chance to think about the possibilities of networking?

Al: Yes. It’s interesting that Lisa had networking but it was never shipped. So they had a local area networking called Applenet. The only use that was ever made of it was in the factory for burn-in testing. But it was interesting that Apple had networking about the same time the DEC, Intel, and Xerox released the Ethernet.

Paula: Did it have any ability to play music or produce sound?

Al: Not normally, Alan Kay’s group interfaced an organ keyboard. They had a synthesizer program that Ted Kaehler wrote. Most of the machines didn’t have sound. There was research in the early [19]80s to integrate telephone functionality into the machine, which evolved into PARC’s Etherphone project.

Paula: How long has it taken you to restore the two Altos, including the disk packs?

Al: I’ve been working on it since the beginning of March, so that has been two months of steady work. There is lots of deterioration of foam in the machines. All the filters had deteriorated. So I had to fabricate new filters and then go through with a vacuum and clean out all the bits of decomposed filters in the machine. Then inspecting all the cards, cleaning contacts and things, was necessary. The most complicated [task] was probably the restoration of the monitors. Because the phosphors are long-persistence, they tend to burn in. So it’s really hard to find CRTs [cathode ray tubes] that have been used that are in good condition because there are almost no used CRTs out there. Alto CRTs haven’t been in production at all for about 15 years. So you can’t buy new CRTs. So what I ended up doing on the Museum’s machines was I restored two CRT monitors of my own that I had bought 15 years ago. Then I took the best used CRTs I had and put them in the Museum’s displays so that is why one is dimmer then other, because there is some burn out.

Deflection coils.

Paula: Explain some of other issues around the CRTs. Earlier you mentioned how the wires were corroded.

Al: Sure. There was a problem on one of them where the monitor was stored in a damp environment. So the horizontal and vertical deflection coils are made of copper wire and at the point where they bend a corner around on the yoke they had turned green from exposure to water. I ended up having to clean the edge of yoke and then reinsulated it.

Paula: How long did it take just to clean that part of the CRT with the corroded wires?

Al: About two days.

Paula: Interesting that just one little piece took two days.

Al: Yeah and then, the monitors tended to run kind of warm. So there are lots of components, especially capacitors inside of the monitor that needed to be replaced. Just because they had turned brown and changed value. So I ended up changing a bunch of capacitors on the board.

Paula: Did you need to fabricate the capacitors?

Al: No you can still buy them. There is a coil inside that ran really hot and I needed to replace those. I was able to find replacements from a company who had bought the back stock from Ball Brothers Research, who had originally made the monitors.

Paula: So you’re mostly getting parts from original companies or others who had purchased the original companies when the Alto was originally built in the [19]70s?

Al: There are a fair number of parts you can get modern equivalents for, so I used those. In cases where there are no modern equivalents, I either tried to find replacements or match something that was close.

Left: Overheated and good inductors. Right: Overheated (top) and replacement components (bottom).

Paula: Did it take time to find the vendors?

Al: If something is on the web, it’s pretty easy to find. Most components companies have some kind of web presence now.

Paula: Tell me a little about cleaning the screens? You were cleaning their edges.

Al: The CRTs themselves were okay. I didn’t have any problems with what people call “screen rot,” which is where the adhesive for the safety glass on the front of the CRT looks like it is moldy, but it’s not actually mold. These didn’t have that problem.

Paula: What about the cabling and power supplies? I know they can disintegrate over time.

Al: The power supplies were a problem, so I had to find replacement filter capacitors for them then go through and clean and check all the parts inside, then burn them in for a while on an electronic test load outside of the computer. Then I run the machines for days at a time to make sure there isn’t any kind of component failure while it’s running. I had a week or two when they weren’t reliable and they’ve been slowly getting better as I’m replacing marginal components.

Paula: How much detective work is it to ferret out the marginal components?

Al: It’s not too bad because you can generally isolate it to a particular board. Since we have multiple machines running I can swap boards to see if the problem moves. So then I know how to isolate the problem. It turns out that I’ve been restoring these for probably 30 years but didn’t have access to any Ethernet connectivity before I was able to get circuit boards from LCM+L [Living Computer: museum + lab, formerly the Living Computer Museum]. It turns out the most problematic part in the whole machine is the disk drive. So I’ve had problems where I’d turn the machine on and it wouldn’t boot. And it turns out it’s just the disk drive being flaky.

Paula: And that’s much easier?

Al: It eliminates the disk drive from the equation. And what I found is when a machine won’t boot when it’s cold, it’s actually the disk drive. It will boot fine, if you boot across the Ethernet. Which was an interesting thing to discover.

Left: Al’s workspace. There’s always something being fixed! Right: A sample circuit board.

Paula: So how many other people are currently restoring Altos?

Al: There are quite a few considering as there are so few machines left. I know there is someone in England now trying to restore a machine that the University of Cambridge has. I haven’t heard from them lately. There is the group that restored the Y Combinator machine. Now they are working on Bruce Damer’s machine. And then Josh Dersch and the folks up at LCM have restored machines and they have been doing a lot of work over the years.

Paula: Would you say this is a community effort, not just a CHM effort?

Al: Definitely. There are folks doing the Y Combinator and a lot of work with Josh at LCM and myself.

Paula: This is an interesting lesson in restoring old computers. That is if you do it right, it takes a lot of people.

Al: And then the amount of spare parts that I’ve collected over the last 30 years. Both Y Combinator’s and Bruce Damer’s machines were missing circuit boards, so I was able to get spare boards to them. Otherwise they would have been totally stuck with missing circuit boards.

Paula: I know there were a number of problems getting the software to work. Was this a disk drive issue or other issues as well?

Al: There was a problem with the Ethernet interface board that LCM developed that it could read Ethernet packets but couldn’t send them out correctly. So that probably caused about a three week delay when we were trying to figure out why that was going on. I ended up sending my hardware back up to LCM and then they updated the firmware in the board. So we got that working about one and half weeks ago. So once I had that working I made a lot of progress. So I’m now in the process of making up the cabling that the CHM machines are going to use. Getting the Ethernet connected and then getting another server running for serving Ethernet files to the CHM machines. [I’m] starting to go through the Museum’s disk packs. Up to about a week ago, I had been working with a single disk pack of mine. Now I’ve started to go through my disk packs and CHM’s packs to see which ones are actually usable. They need to be inspected and if there are bad spots on them—identify that. That’s all visual, and if you’re relatively certain the disk pack is clean you can put in a disk drive and scan across the surface to see if there is any flaws detected. But most of these packs are 30 or more years old now. Some haven’t been stored in very good conditions, so there is some oxidation and corrosion on the packs which is not good.

Left to right: Two Alto disk drives, disk packs, and Interior shot of the disk.

Paula: I’m assuming that there is really nothing you can do with corrosion on the pack?

Al: Right. The trick is to just find media that is still clean. So one of the things that is fairly time consuming is to go through every pack and examine them with a fiber optic light and sometimes an eye loop. So it takes about half hour per pack. Then there is a way to transfer the data that is on a disk pack across the Ethernet. So if there are any packs I’ve come across that I haven’t already archived, once I inspect them, I try to read them.

Paula: So you’re transferring it over the Ethernet and storing it on a modern hard drive?

Al: Right. Those images can be used with Josh’s ContrAlto emulator. I have some programs that can make directories and things like that.

Paula: Are you keeping some kind of structure through directories?

Al: A large number of the packs were read back in 2001. So I need to go through and take pictures of the labels and then make a directory listing of the contents and then get that all together and put it in the Museum’s digital repository.

Paula: This is the next stage to make sure the software is preserved?

Al: Right.

Inspecting the disk.

Paula: Do you think there is any way to easily make it accessible to the outside world?

Al: Lots of people can use it with Josh’s ContrAlto emulator. So there is a fair amount of interest in finding more software. And Josh is working on getting some really old software that doesn’t work on modern Altos. He has been working on getting Ted Kaehler’s music program running in emulation over the last couple of weeks.

Paula: So reading the disk packs from various collections and making that available could open up a lot of exploration and research?

Al: My main concern is making sure there is no personal information on any of the disk packs that are released.

Paula: Is there any particular piece of software that really surprised you as you’ve been working with the disk packs or anything in general?

Al: There are some things that I haven’t really looked at in 30 years and [have] forgotten about. So it’s interesting to come back around to this and then to have a machine in good condition with a clear bright screen with a properly working mouse and keyboard. Then just kind of making a laundry list of things I’d like to play with or I remember looking at but just not having the time or a machine to be able to do that. Then all the work that Josh has done and being able to work at my desk and go back through all the stuff that has been collected but hasn’t been accessioned or looked at.

Paula: Would you have been able to complete these restorations without saving all the circuit boards, documentation, and CRTs?

Al: Certainly not as fast as I did. It’s very difficult to do any of these restorations without the documentation because they are fairly complicated machines. And then having the emulators is helpful too. Because you can test to see if software is working before you get the actual hardware working. And then there is all the work that Paul McJones did to make the stuff that was recovered from the PARC Alto CD in an actually in a usable form.

Paula: What is your takeaway from the entire experience?

Al: That it takes a lot longer than you think when you start. I had the machines basically running within the first couple of weeks once I started working on them and then it’s just been weeks and weeks and weeks of either waiting for parts or getting through the laundry list of little things like making cables and checking disk packs. It just takes a lot of time. It’s a fairly fast process but there are lots of little pieces you need to do. It tends to be I’ll pick something that needs to be done and spend an hour or two on it and be done then go to the next thing.

Paula: Do you have any final thoughts for other restorers?

Al: Mostly just to be concerned about all the electro-mechanical parts. It’s pretty much the usual problem with old electronics, where things get corroded or connectors get intermittent and then trying to be careful not to damage anything while you’re cleaning it. And then just be slow, patient, and methodical in how you do the work. The one thing I’m really bad at is writing notes. So I didn’t keep a log book while I was working on this, mostly because I was working on four machines in parallel. And it was kind of working on this block of things for this part of the machine and then going on and doing the next part. Then having to wait for parts or run out to the hardware store or something to get cleaning supplies or things. So there are just all these bits and pieces that are going on concurrently.

Paula: Is there anything else you want to add?

Al: No, I think those are the main things. The Museum’s policy of not restoring things that we only have one of is a good idea because it’s really easy to break something if it’s old and it’s mechanical. If you’re not really careful, you can strip or break something. If you only have one, you don’t have another one to compare it to.

Paula: So, really if you only have one [of something], you want to preserve the integrity of that one for study and not restoration? That makes perfect sense in a museum environment.

Al: Yes. Or to evaluate the condition of these two things. Mostly of mechanical things where something will wear or rubber will deform or sometimes you don’t know what the original was supposed to look like. So if you still have another example of the thing that hasn’t been touched you have a better chance of being able to reproduce it. Assuming there isn’t physical documentation somewhere.

Paula: Al, it has been fascinating to hear about your dedication and patience in restoring the Altos. I’m equally appreciative of the truly remarkable Alto computer. Thank you for taking the time.

Screenshots running on a restored Alto. Top (left to right): Kaleidoscope, Puzzle, and Pac-Man. Bottom (left to right): Maze, Pinball, and Billiards.

Related Xerox PARC Oral Histories & Collections

• Adele Goldberg Oral History (video), Interviewed May 5, 2010
• Collected Papers of Adele Goldberg, 1973-2010
• Chuck Thacker Oral History (transcript), Interviewed August 29, 2007
• Butler Lampson Oral History, Interviewed August 22, 2006
• Bob Metcalfe Oral History, Part 1 (video) Interviewed November 29, 2006
• Bob Metcalfe Oral History, Parts 1 & 2 (transcript), Interviewed November 29, 2006 and January 31, 2007
• Alan Kay Oral History (transcript), Interviewed November 5, 2008

Other Restorations

• ContrAlto, Alto emulator at the Living Computer: museum + labs
• Bruce Damer’s DigiBarn collection
• Y Combinator restoration

The post Restoring Yesterday’s “Computer System of Tomorrow”: A Conversation with Curator & Xerox Alto Restorer Al Kossow appeared first on CHM.