Our Machines, Our Selves

A pair of public lectures kick off the new Mellichamp Initiative in Mind & Machine Intelligence
Tuesday, February 11, 2020 - 09:30
Santa Barbara, CA


Pixellated image of man blurs the line between man and machine

Artificial intelligence blurs the line between man and machine

Photo Credit: 

Matt Perko, UC Santa Barbara

Miguel Eckstein.jpg

Miguel Eckstein

William Wang.jpg

William Wang

William Wang

Photo Credit: 

Courtesy image

We live in a time of convergence of human and machine. Our human experience is augmented by machine applications, from internet-enabled sensors to human-assistive robotics, while we imbue our machines with human qualities, including context-awareness, vision and artificial intelligence (AI).

As technology brings us and our computers into an ever more seamless existence, we seek to understand our place in the complex relationship between human and machine intelligence. Enter UC Santa Barbara’s new Mellichamp Academic Initiative in Mind & Machine Intelligence, a multi-year research effort made possible by a generous gift from Duncan and Suzanne Mellichamp.

The overarching goal of the initiative is to identify the strengths and capabilities of both human and machine intelligence, in order to use the best of one to augment and benefit the other.

“It seems only natural for our society to ask these deep questions about AI and the human mind, and also to think of bold, new questions,” said Miguel Eckstein, a professor in UC Santa Barbara’s Department of Psychological and Brain Sciences. “The fascination with the impact of intelligent machines on human life and society, with understanding the limits of artificial intelligence and with pinpointing what is unique about the human mind has been around for many years and has involved scientists, philosophers, futurists and science fiction writers. With every new leap in the development of AI, we seem to return to these questions.” 

Joining Eckstein at the helm of this endeavor is UC Santa Barbara computer science professor William Wang, an expert in natural language processing (NLP) — a discipline of artificial intelligence that seeks to teach computers to understand and communicate using human language in text and verbal form. Rapid advances in the field have brought us closer to our computers than ever.

On February 19 and 20, the public is invited to explore these big questions in two talks presented as part of a workshop to kick off the new intiative. The hour-long lectures will begin at 5 p.m. in the campus’s Marine Science Institute auditorium. The lectures are free and open to the public, although registration is encouraged.

The Barrier of Meaning (Feb. 19)

Register here:


As machines gain complexity and even superiority in some tasks, and as we increasingly entrust them with important decisions and give them autonomy, there remains one crucial realm in which humans reign supreme: understanding and deriving the meaning of things. It’s an obstacle explored in countless ways, from philosophical texts to science fiction films, and often is seen as the dividing line between mere computation and true intelligence in computers.

Melanie Mitchell will tackle the “barrier of meaning” (a term coined in 1986 by mathematician and philosopher Gian-Carlo Rota) in her talk “Can Analogy Unlock AI’s Barrier of Meaning?” According to Mitchell, analogy — the associations and comparisons we make between concepts and objects — may be the key that unlocks that door. In her talk, she will draw on her research on conceptual abstraction, analogy-making and visual recognition in artificial intelligence systems to reflect on the role played by analogy-making at all levels of intelligence — and on how analogy-making abilities will be central in developing AI systems with humanlike intelligence.

Mitchell is the Davis Professor of Complexity at the Santa Fe Institute and a professor of computer science (currently on leave) at Portland State University. She has authored or edited six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science and complex systems.

The Rise of Automation (Feb. 20)

Register here: https://tinyurl.com/mindandmachine2

It’s a question as old as the Industrial Revolution and it remains just as important today: Will the machines take all our jobs? In his lecture “Bots and Tots,” Google chief economist Hal Varian will delve into issues involved in forecasting attempts to predict the impact of automation on the demand for human labor in the next few decades. He will also discuss how the supply side of the market interacts with the demand side.

In addition to his work at Google, Varian is an emeritus professor at UC Berkeley in the departments of business, economics and information management. He has published numerous papers in economic theory, econometrics, industrial organization, public finance and the economics of information technology.

The public lectures are part of a larger, research-focused, two-day workshop that aims to bring together some of the greatest minds on the topic of human and machine intelligence in a series of interdisciplinary interactions. Researchers from leading institutions including Harvard, Princeton, UC Berkeley, Carnegie Mellon, Google, University of Chicago Business School and Facebook AI will be among the participants, providing insights from a variety of fields, including computer science, engineering, psychology, neuroscience and economics.

“Interdisciplinary meetings are fundamentally different from the more typical meetings,” said Eckstein, whose own research delves into the ways human brains conduct visual searches, recognize faces and direct attention — tasks humans do naturally, but that computers still struggle with. “Everybody needs to work a little harder to understand each other and concepts and approaches get shaken.”

The workshop’s meetings and discussions will give researchers the lay of the land by focusing on the similarities and differences in the capabilities of human and artificial intelligence, and the state of the art on AI that aims to achieve some of the mind’s unique abilities. It will also look at the role of AI in the economic world.

“How much screen time do we spend on our cellphones each day? Do you ask Alexa for the traffic?” asked Wang, who is also the director of the campus’s Center for Responsible Machine Learning (CRML). “The convergence of human and machine intelligence is already happening, and removing the blocks to communication would free up human time and energy, allowing us to think about more important questions.”

The explorations will continue beyond the workshop as well, with research collaborations bringing together faculty members from diverse disciplines, including four endowed chairs. The initiative also will bridge myriad centers and programs on campus, including the Sage Center for the Study of the Mind, CRML, the Cognitive Science Program, the Data Science Initiative and the Center for Information Technology and Society.

“UCSB has built a worldwide reputation by looking at important scientific problems from different perspectives and it was conducting interdisciplinary research before that became a trend,” Eckstein said. “We are approaching this initiative with the same philosophy. Our goal is to create a cluster of professors and researchers that like to get together, look at problems from very different perspectives and think hard about new questions and new approaches to answer those questions.”

The Mellichamp Academic Initiative in Mind & Machine Intelligence is part of a special new cluster that will include four endowed chairs. These will have connections to multiple academic departments, including psychological and brain sciences, economics, geography, electrical and computer engeineering, linguistics and English, as well as to neuroscience and data science initiatives.

Contact Info: 

Sonia Fernandez

(805) 893-4765