The Great Progression Series: The Actual Risks of Generative AI
After two events that dazzled our imaginations and broke our conventional boundaries, the third and final session of the Great Progression Series laid out actual risks of this breakthrough capability that we call generative AI.
Complacency
Dazza Greenwood, executive director of the MIT Computational Law Report, warned of creating dependency on AI to the extent that we accept “good enough,” then copy-paste. For a supercharged QA process, it has vast benefits. However, in hospital rooms, cockpits, classrooms, and more, we need an “immune system” so we don’t neglect the importance of critical thinking.
Narrowing in on what matters
Peter Leyden provided guidance on risks commonly discussed publicly versus real, imminent risks. Given the energy of the crowd — founders, investors, policymakers, academics — the list, while not exhaustive, helped navigate past what is interesting to pontificate and home in on what we must work on today to mitigate.
The topic drew in the diversity of a crowd that we’ve come to expect, including a senior adviser to the US Secretary of Commerce, founder of Credo.ai, chair for Future of Work at Singularity University, the White House Innovation Fellow, a partner from Mindful VC, ethics council members, and many others.
Those with decades of experience in research, policy, and enterprise often reference history to project how to prepare. In the era of generative AI, however, it’s evident that the magnitude of impact and implications is something we haven’t seen before.
Jerry Kaplan, who invented the tablet and authored entrepreneurial books, such as Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence, shared his concern about the disruption to human relationships. For example, an endlessly patient companion can lead to emotional dependency and a world where machines are consulted first for compassion, not just information.
Reflecting on the spectrum of topics from an even wider collection of diverse perspectives, I found the discussions to not be over-rotated in optimism or existential panic. The possibilities are real and inspiring, but so are the risks.
Two new components of generative AI to address:
1. The gap between expectations and understanding
The tidal wave of popularity is creating dissonance in how we view, learn, and apply this capability. We need to close the gap by increasing our discipline to learn at a pace greater than ever before. The only way to do this is by communicating at a greater level to match. As Kevin Kelly states, “Nobody is as smart as everybody.”
2. Establishing liability
Generative AI (GenAI) is as accessible as an Excel workbook; however, the power of GenAI is as great as a having infinite interns. Our conventional methods of governance for powerful tools (think driver licenses, certifications, age limits) do not apply yet. The creators of these tools are calling for regulation and policymakers are asking for help. As Earl Comstock says, we all should help define what “liability” means in this new era of generative AI. Otherwise, we may find ourselves holding the wrong entity accountable, leading to ineffective legislation with undesirable consequences.
The benefit of generative AI is unquestionable. The productivity gains are monumental; AI gives us a lever to expand the precious hours and minutes in a day. Going back to Dazza’s statement on seductive automation, it’s critical we use the added time to revisit our purpose, whether that’s individual or organizational. We have the opportunity to apply the newfound capacity to innovate beyond conventional constraints.
An evolution
At Slalom, we introduced the Power of Paradox to challenge what we historically accepted as mutually distinct realities — such as sustainability and abundance, innovation and tradition, timeless and modern — to evolve industries, domains, and humanity. Max Ernst, a German artist and poet, once said, “Creativity is that marvelous capacity to grasp mutually distinct realities and draw a spark from their juxtaposition.” We are excited to break difficult trade-offs and evolve humanity.
For more on the Great Progression Series, read this recap from founder Peter Leyden.
Slalom is a global consulting firm that helps people and organizations dream bigger, move faster, and build better tomorrows for all. Learn more about Slalom’s human-centered AI approach and reach out today.
