Notes from Transform.AI - Part 3: Technology Alone is Not Enough
By Kathryn Hume, Sep 19, 2017
I spent the a few days in June at Transform.AI in Paris, a European conference designed for c-level executives managed and moderated by my dear friend Joanna Gordon. This type of high-quality conference approaching artificial intelligence (AI) at the executive level is sorely needed. While there’s no lack of high-quality technical discussion at research conferences like ICML and NIPS, or even part-technical, part-application, part-venture conferences like O’Reilly AI, ReWork, or the Future Labs AI Summit (which my friends at ffVC did a wonderful job producing), most c-level executives still actively seek to cut through the hype and understand AI deeply and clearly enough to invest in tools, people, and process changes with confidence. Confidence, of course, is not certainty. And with technology changing at an ever faster clip, the task of running the show while transforming the show to keep pace with the near future is not for the faint of heart.
Transform.AI brought together enterprise and startup CEOs, economists, technologists, venture capitalists, and journalists. We discussed the myths and realities of the economic impact of AI, enterprise applications of AI, the ethical questions surrounding AI, and the state of what’s possible in the field. Here are some highlights.1
Technology Alone is Not Enough: The End of The Two Cultures
I remember sitting in Pigott Hall on Stanford Campus in 2011. It was a Wednesday afternoon, and Michel Serres, a friend, mentor, and âme soeur,2 was giving one of his weekly lectures, which, as so few pull off well, elegantly packaged some insight from the history of mathematics in a masterful narrative frame.3 He bid us note the layout of Stanford campus, with the humanities in the old quad and the engineering school on the new quad. The very topography, he showed, was testimony to what C.P. Snow called The Two Cultures, the fault line between the hard sciences and the humanities that continues to widen in our STEM-obsessed, utilitarian world. It certainly doesn’t help that tuitions are so ludicrously high that it feels irresponsible to study a subject, like philosophy, art history, or literature, that doesn’t guarantee job stability or economic return. That said, Christian Madsbjerg of ReD Associates has recently shown in Sensemaking that liberal arts majors, at least those fortunate enough to enter management positions, end up having much higher salaries than most engineers in the long run. (I recognize the unfathomable salaries of top machine learning researchers likely undercuts this, but it’s still worth noting).
Can, should, and will the stark divide between the two cultures last?
Transform.AI attendees exhibited few points in favour of cultivating a new fusion between the humanities and the sciences/technology.
First, with the emerging interest paid to the ethics of AI, it may not be feasible for non-technologists to claim ignorance or allergic reactions to any mathematical and formal thinking as an excuse not to contribute rigorously to the debate. If people care about these issues, it is their moral obligation to make the effort to get up to speed in a reasonable way. This doesn’t mean everyone becomes literate in Python or active on scikit-learn. It just means having enough patience to understand the concepts behind the math, as that’s all these systems are.
Next, as I’ve argued before, for the many of us who are not coders or technologists, having the mental flexibility, creativity, and critical thinking skills awarded from a strong (and they’re not all strong…) humanities education will be all the more valuable as more routine, white-collar jobs gradually get automated. Everyone seems to think studying the arts and reading books will be cool again. And within Accenture’s triptych of new jobs and roles, there will be a large role for people versed in ethnography, ethics, and philosophy to define the ethical protocol of using these systems in a way that accords with corporate values.
Finally, the attendees’ reaction to a demo by Soul Machines, a New Zealand-based startup taking conversational AI to a whole new uncanny level, channeled the ghost of Steve Jobs: “Technology alone is not enough—it’s technology married with liberal arts, married with the humanities, that yields us the results that make our heart sing.” Attendees paid mixed attention to most of the sessions, always pulled back to the dopamine hit available from a quick look at their cell phones. But they sat riveted (some using their phones to record the demo) when Soul Machines CEO Mark Sagar, a two-time Academy Award winner for his work on films like Avatar, demoed a virtual baby who exhibits emotional responses to environmental stimulai and showed a video clip of Nadia, the “terrifying human” National Disability Insurance Scheme (NDIS) virtual agent enlivened by Cate Blanchett. The work is really something, and it confirmed that the real magic in AI arises not from the mysteriousness of the math, but the creative impulse to understand ourselves, our minds, and our emotions by creating avatars and replicas with which we’re excited to engage.
Actress Cate Blachett as a “trainer” in the new AI economy, working together with Soul Machines.
Most specific names and references are omitted to respect the protocol of the Chatham House Rule. ↵
Reflecting on the importance of the lessons Michel Serres taught me is literally bringing tears to my eyes. Michel taught me how to write. He taught me why we write and how to find inspiration from, on the one hand, love and desire, and, on the other hand, fastidious discipline and habit. Tous les matins – every morning. He listed the greats, from Leibniz to Honoré de Balzac to Leo Tolstoy to Thomas Mann to William Faulker to himself, who achieved what they did by adopting daily practices. Serres popularized many of the great ideas from the history of mathematics. He was criticized by the more erudite of the French Académie, but always maintained his southern soul. He is a marvel, and an incredibly clear and creative thinker. ↵
Serres gave one of the most influential lectures I’ve ever heard in his Wednesday afternoon seminars. He narrated the connection between social contract theory and the tragic form in the 17th century with a compact, clever anecdote of a WW II sailor and documentary film maker (pseudo-autobiographical) who happens to film a fight that escalates from a small conflict between two people into an all out brawl in a bar. When making his film, in his illustrative allegory, he plays the tape in reverse, effectively going from the state of nature – a war of all against all – to two representatives of a culture who carry the weight and brunt of war – the birth of tragedy. It was masterful. ↵
About the author
Kathryn Hume is VP Product & Strategy at integrate.ai, a SaaS startup applying AI to a unique combination of social, behavioral, and enterprise transaction data to help large B2C businesses optimize customer engagement. Alongside her work at integrate.ai, she is a Venture Partner at ffVC, a seed- and early-stage technology venture capital firm, where she advises early-stage artificial intelligence companies and sources deal flow. While at Fast Forward Labs, Kathryn helped Fortune 500 companies accelerate their machine learning and data science capabilities. Prior to that, she was a leader in Intapp’s Risk Practice, focused on data privacy, security, and compliance. A widely respected speaker and writer on AI, Kathryn excels at communicating how AI and machine learning technologies work in plain language. Kathryn has given lectures and taught courses on the intersections of technology, ethics, law, society at Harvard Business School, Stanford, the MIT Media Lab, and the University of Calgary Faculty of Law. She speaks seven languages, and holds a PhD in comparative literature from Stanford University and a BA in mathematics from the University of Chicago.
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