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Nela Richardson speaks at our spring workshop


Recap: Our Spring 2022 Workshop
Avoiding the Turing Trap

Stanford Digital Economy Lab Spring 2022 Workshop: Avoiding the Turing Trap

Stanford University
April 19, 2022

Photography by Christine Baker

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What will the workplace look like in 20 years with the rise of artificial intelligence and other digital technologies?

We find ourselves asking this question a lot at the Lab. And for the most part, we’re optimistic about AI’s impact on society. But there is cause for concern, especially if businesses and technologists focus mostly on using AI to automate existing tasks rather than augment human capabilities.  

In the spring of 2022, the Lab brought together researchers and experts for our first-ever in-person event to explore the dangers of incentivizing automation far more than augmentation – something we call “the Turing Trap.” 

The daylong workshop featured interactive panel discussions and presentations by Lab-affiliated researchers showcasing their recent work. Lab Director Erik Brynjolfsson opened the event by framing the opportunities and challenges of human-like AI. Nela Richardson, chief economist at ADP, closed the day with her keynote address, “AI’s People Problem.”

The top-line takeaway from the event? AI can positively benefit the future of work and society. However, we must focus on issues such as bias and economic inequality, and be mindful of the dangers of prioritizing automation over augmentation to achieve that goal.

Session 1 | Introduction

The Turing Trap: The Perils and Promise of Human-Like

Erik Brynjolfsson, Stanford Digital Economy Lab
Erik Brynjolfsson talks
Stanford Digital Economy Lab Director Erik Brynjolfsson opened the workshop with a talk about the perils and promise of human-like AI.

Not all types of artificial intelligence are human-like—in fact, many of the most powerful systems are very different from humans—and an excessive focus on developing and deploying human-like AI can lead us into a trap, says Erik Brynjolfsson, director of the Stanford Digital Economy Lab.

Brynjolfsson opened our spring workshop with his presentation, “Avoiding the Turing Trap: The Promise and Peril of Human-like AI.”

Related article: “The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence

The Turing Trap: The Promise and Peril of Human-like AI

37 minutes

Session 2 | Panel Discussion

Reaping the Benefits of AI in the Future of Work

Laura Tyson, UC. Berkeley
Kevin Scott, Microsoft
Nicol Turner Lee, The Brookings Institution
Steve Lohr, The New York Times (Moderator)
Steve Lohr, Kevin Scott, Nicol Turner Lee, and Laura Tyson participate in a panel discussion at the Stanford Digital Economy Lab Spring 2022 Workshop
L-R: Steve Lohr, Kevin Scott, Nicol Turner Lee, and Laura Tyson.

In our first panel of the day, “Reaping the Benefits of AI in the Future of Work,” panelists discussed some of the current methods used to develop human-centered technology and the difficult task of implementing technology that augments rather than automates. They also explored what stakeholders from across academia, industry, and policy can do to direct AI development toward more human-centered outcomes.

Session 3 | Exhibition

Exhibition I

Scott Phoenix, Vicarious
Scott Phoenix presents at the Stanford Digital Economy Lab Spring 2022 Workshop
Scott Phoenix of Vicarious.

Scott Phoenix is co-founder. of Vicarious, the California-based startup that’s using the computational principles of the brain to build software that can think and learn like a human.

Session 4 | Fireside Chat

Special Issue of Daedalus on AI and Society

David Oxtoby, American Academy of Arts and Sciences
James Manyika, Google
David Oxtoby and James Manyika at the Stanford Digital Economy Lab Spring 2022 Worksho
David Oxtoby and James Manyika discuss the latest issue of Daedalus.

David Oxtoby and James Manyika took a deeper dive into “AI & Society,” the spring 2022 issue of Dædalus that explores AI’s effects on labor and the economy, its relationship with inequalities, its role in law and governance, its challenges to national security, and what it says about us as humans.

“Why are we focusing so obsessively on the sets of tasks that are actually easy for humans, but hard for machines? Isn’t that exactly backward? We should be focusing on the things that are hard for humans and easy for machines.”

Erik Brynjolfsson

Erik Brynjolfsson

Director, Stanford Digital Economy Lab

Session 5 | Fireside Chat

AI in 2050: What Went Right?

Eric Schmidt, Schmidt Futures
James Manyika, Google
Eric Schmidt
Eric Schmidt of Schmidt Futures.

Eric Schmidt and James Manyika time-traveled into the future to imagine how AI would be a benefit to the society in the year 2050. The pair discussed what we must do now and in the future to overcome certain pitfalls and obstacles, such as bias, inherent with AI, machine learning, and other digital technologies.

Session 6 | Exhibition

Exhibition II

Jack Clark, Anthropic
Jack Clark, Anthropic
Jack Clark of Antrhopic.

Jack Clark co-founded Anthropic, an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems.

Session 7 | Panel Discussion

Beyond the Turing Test: Benchmarking AI

Jack Clark, Anthropic
Gillian Hadfield, University of Toronto
Stuart Russell, UC Berkeley
David Kanter, MLCommons (Moderator)
L-R: Jack Clark, Stuart Russell, Gillian Hadfield, David Kanter

Benchmarks can have exceedingly high leverage in shaping a field. In the field of AI, a clear set of standards can accelerate progress and help guide it toward beneficial and inclusive outcomes. In this discussion, panelists touched on a range of conceptual and specific AI benchmarks that have the potential to shape the future of AI and its impacts on humanity.

Session 8 | Exhibition

Exhibition III

Zayd Enam, Cresta
Zayd Enam of Cresta.

Zayd Enam co-founded Cresta, a company that helps people learn high-value skills using artificial intelligence.

Lindsey Raymond

Lindsey Raymond | Augmented Intelligence: The Effects of AI on Productivity and Work Practices

Sarah Bana | work2vec: Using Language Models to Understand Wage Premia

Victor Yifan Ye | Could a UBI Solve Automation’s Inequality Problem?

Mina Lee and Zanele Munyikwa

Mina Lee and Zanele Munyikwa | The Economic Impact of Foundation Models on Writing​

Dan Sholler | The Future of Work in California: Thinking Regionally About Technology and Inequality

Session 10 | Keynote

Keynote: AI’s People Problem

Nela Richardson, ADP
Nela Richardson of ADP delivers her keynote address.

Nela Richardson, chief economist at ADP, closed the workshop with her keynote address, “AI’s People Problem.” Richardson talked about the relationship between artificial intelligence, data, and the labor market. “The problem is AI is only as good as the data that powers it,” she said.

Keynote by Nela Richardson:
AI’s People Problem

28 minutes

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