AI

Feedback: Spring 2024

Anonymous — Mon, 04 Mar 2024 07:00:00 +0000

Feedback: Spring 2024 Anonymous (not verified) Mon, 03/04/2024 - 00:00

Casa Bonita Musings

$40 million? We could build a new health clinic for outpatient care, with a welcoming building, a diagnostic testing laboratory, an X-ray department, a pharmacy, plenty of examination rooms with bright lights for the doctors, physicians assistants, nurses and patients, conference rooms and staff offices, a comfortable sunshine-filled waiting room, plus all of the equipment needed, large and small, down to the last bottle of rubbing alcohol and canister of fluffy white cotton balls, for $40 million. Just sayin’.

Nancy McCurdy (Mktg’90)
Denver

The current edition of the Coloradan features an article about Trey Parker (DistSt’18) and Matt Stone’s (FilmSt, Math’93) acquisition, renovation and relaunch of Casa Bonita. The article states Mr. Stone as having earned degrees in math and art. This is not accurate: Mr. Stone earned degrees in math (BA) and a BFA in film studies (currently “cinema studies & moving image arts”). We proudly list Mr. Stone as one of our alumni, and would really like to see a correction in your online issue and in your next print issue. The readers of the Coloradan should have accurate news and information about the institution that they so much love and support, and the individual departments should be acknowledged properly.

Ernesto R Acevedo-Muñoz
Professor, Chair, ��ý�Ļ��Ʒ Department of Cinema Studies & Moving Image Arts Boulder

[Editor’s Note: We have updated Matt Stone’s degree information to reflect his film studies degree.]

Our readers also sounded off on social media about the 2023 Casa Bonita renovation:

They did a really great job with the restoration. The food is worth the price, and the entertainment is top-notch.

Eric Anhold (PolSci’00)
Via Facebook

Yay for Matt and Trey and saving Casa Bonita! Always enjoyed it as a kid.

Susan Schlatter (Psych’93)
Via Facebook

Fantastic alumni story.

Chris Rockne (MechEngr’07; MS’07)
Via Facebook

During my four years at CU (1990–94), I recall on several occasions walking past the fine arts building on the way to the UMC from my dorm at Cheyenne Arapaho. I’d see the students on the grass, and I arrogantly thought to myself — “what a bunch of suckers studying art.” Not long after graduating, I learned that two of those actual “suckers” were the geniuses behind the show I was then obsessed with: South Park. I got such a kick out of realizing how stupid I was back then, and I still tell that story to anyone who foolishly tries to reduce someone’s path. Shout out to CU fine arts. And shout out to Matt and Trey for repping the Buffs as good as anyone ever did.

@themiket
Via Instagram

This is so awesome for me — a reminder of fond trips to Casa as a family when I was young, and then even sweetened as I remember reading Matt and Trey’s cartoons when I was at Boulder during the same time.

@carterasc5
Via Instagram

A Gift from Betty Woodman

I worked for Betty Woodman [Origins, Fall 2023], and she gave me a very large teapot at my wedding reception that she attended. I have a photo of her at my reception which would have been about 1970.

Marie McCreery (A&S’67)
Niwot, Colorado

From Casa Bonita to Star Trek

Lovely job — thank you. I really enjoyed your stories on the remodeling and new ownership of Casa Bonita, and on the science advisor for Star Trek.

Sabrina Sideris (Engl, Hist’00)
Niwot, Colorado

The Tiny Hill Diner

It was with something of a shock I opened the fall issue of the Coloradan and saw the photograph of the little diner that sat just across Pennsylvania Street opposite The Sink. For years I have interrogated friends and acquaintances, even Boulder history writers, in search of someone else who remembers this diner. At some point, it simply vanished. I had begun to think of it as a will o’ the wisp.

But here is the Twilight Zone part: Contrary to the account in the Coloradan, I could not have eaten there prior to the summer of ’63, which was when I came to Boulder, and I remember it being the Buff Top Hat Diner.

Now if I can only find someone else who remembers Bennet’s Brick Oven.

Earl Noe (Jour’66)
Boulder

Are We Ready for Self-Driving Cars?

In reference to the Fall 2023 article “Is the World Ready for Self-Driving Cars?,” an image by Sam Gross from page 21 of Everyone’s a Critic: The Ultimate Cartoon Book edited by Bon Eckstein.

Ernst Anton Kemper (ChemEngr’59)
Lakewood, Colorado

Coloradan Shenanigans

I’d like to share my recent experience regarding the alumni magazine. My son Page (CivEngr’05; MS’15) and I are both CU graduates, so we’re both on your list to receive the Coloradan. However, for many years his copy has come to my address. I asked him to notify you of this but he couldn’t be bothered. So, every time it comes, I hand off his copy, usually in a batch of articles I’ve curated for him from magazines and newspapers. When I hand him one of these envelopes, he goes through it, surreptitiously or blatantly, and when he finds the Coloradan he sneaks it back into my stuff, under the windshield wiper or slipped through a cracked-open window of my car. We’ve played this game a looong time.

But this Christmas he took it to the next level. When I visited, he told me to sit down and close my eyes. When he said I could look, there was the cover of the Fall 2023 Coloradan on a shower curtain. Of course, it was his copy, with his name and my address. We laughed and laughed, after which I was left wondering, “How do I top this?”

Clearly, the only way to go one better is to have you print the shower curtain pic in your next issue, and to update his listing to his address!

Without silliness, we are all doomed.

Nancy Ball Weil (Russ’77)
Denver

CU’s First Female Olympians

I’d like to offer a fact check and possible correction on page 65 of the Fall Coloradan.

According to my research, CU ski coach Bob Beattie took over the U.S. ski team in 1962. He created a de facto national training center at CU and most of the men and women lived in Boulder and went to CU. Some were down the road at DU and some not in college, and at least one was too young and went to high school in Boulder. About this time of year they would take “incompletes” in their classes and head to Europe to race, then come back and continue classes in the spring. They also trained at Eldora and on St. Mary’s Glacier. In the spring of 1963, that CU/U.S. program became the core of the 1964 Olympic team. Again Boulder was the epicenter, and most of the team that went to the Innsbruck Games were full or part-time CU students. So, this leads me to believe the note in the Coloradan about Sandy Hildner (A&S’67) [“THEN,” Fall 2023] might not be accurate.

I was on the B team in 1976, did some pro skiing, then helped with the CU skiing program working for then-head coach Tim Hinderman. Later I worked for filmmaker Warren Miller and have been involved in the ski industry in various ways ever since. This includes occasional writing gigs.

David Butterfield (Hum’81)
Ketchum, Idaho

[Editor’s Note: Further research shows that while Sandy Hildner was among CU’s first female Olympians, she was not necessarily the first. We regret the reporting error.]

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Photos courtesy Nancy Ball Weil (shower curtain); Marie McCreery (Woodman photo); Casa Bonita
Illustration by Sam Gross from Everyone's a Critic by Bob Eckstein © 2019; Used with permission from Chronicle Books LLC, San Francisco.

Casa Bonita, automatic cars and nostalgic memories.

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Making AI a Tool for Good

Anonymous — Mon, 06 Nov 2023 07:00:00 +0000

Making AI a Tool for Good Anonymous (not verified) Mon, 11/06/2023 - 00:00

Phil Distefano

As developments in artificial intelligence make headlines every week, I often find myself with more questions than answers on the topic.

What are the capabilities and limitations of AI, and how will they evolve as the technology matures? How can students and educators leverage these powerful tools to benefit learning and critical thinking? What happens when individuals use artificial intelligence for nefarious purposes?

It’s easy to default to hesitancy or fear when facing such expansive questions. But during my career in higher education, I have determined that it’s far better to embrace technological change — warts and all — than to resist it. The way we respond to and interact with emerging technologies, in large part, will determine whether they ultimately help or harm.

It’s exciting to consider how artificial intelligence is already changing the way we teach, learn and innovate. ��ý�Ļ��Ʒ faculty, staff and students are at the forefront of this work, harnessing AI to improve autonomous vehicles, enhance K-12 education and create never-before-seen works of art.

Perhaps most exciting, from an educator’s perspective, is that using and developing artificial intelligence is inherently interdisciplinary, requiring perspectives from science, engineering, humanities, business and more. It fosters the kind of freewheeling, unfettered and creative thinking that ��ý�Ļ��Ʒ graduates need for successful professional careers.

Because the potential uses of AI are sobroad, ��ý�Ļ��Ʒ’s Center for Teaching and Learning offers training and support for faculty as they consider whether and how to employ AI tools in their curriculum.

The advent of generative AI tools like ChatGPT — which has been known to churn out biased, racist and inaccurate responses to queries — also illuminates the importance of deepening our university's commitment to diversity, equity and inclusion as we integrate AI into our educational practices.

Now more than ever, we need students, faculty and staff whose backgrounds and perspectives reflect the full spectrum of our society so the technologies that AI underpins are as accessible, equitable and trustworthy as possible. Fighting against bias and misinformation while supporting fact-finding and truth-telling is a critical part of a university's role in sustaining democracy and developing ethical leaders, whether we’re using AI or not.

AI may be the newest tool disrupting our society, but it certainly won’t be the last. And it will take all of us, working together across disciplines, to ensure that it becomes a tool for good.

Philip P. DiStefano is the 11th chancellor of ��ý�Ļ��Ʒ. He is the Quigg and Virginia S. Newton Endowed Chair in Leadership, overseeing ��ý�Ļ��Ʒ’s leadership programs.

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Photo by Casey A. Cass

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A New Way of Learning in the Classroom

Anonymous — Mon, 06 Nov 2023 07:00:00 +0000

A New Way of Learning in the Classroom Anonymous (not verified) Mon, 11/06/2023 - 00:00

Christie Sounart

Sidney D’Mello is a professor in ��ý�Ļ��Ʒ’s Institute of Cognitive Science and Department of Computer Science. He is also director of the National Science Foundation AI Institute for Student-AI Teaming, which aims to develop artificial intelligence (AI) technologies to facilitate social and collaborative learning experiences for all students.

Can you talk about your research with AI and education?

There are five flagship NSF research institutes that focus on supporting learning with AI, and we were the first one. Schools right now haven’t changed in a hundred years — they’re focused on efficiency as an outcome. The use of AI in education has been to keep that vision of efficiency going where students individually work with computer programs powered by AI.

The vision I want for classrooms is a place where students are working together, being loud, and it’s a noisy, rambunctious environment where they’re challenging ideas, and they’re building social relationships. This vision is centered around a different perspective of learning, which is that learning is authentic to students’ interests and identities and so on. A key question we ask is how best to integrate AI within that vision.

How could your vision be implemented?

This is a vision that’s been articulated forever in the learning sciences, but it is difficult for teachers to implement because they can’t be listening in on several student groups at once. Some conversations may go off track, or perhaps some conversations are amazing, but the teacher is unaware of the discussion happening. So the question is, how can AI help support this?

Our idea is thinking of AI as this social collaborative partner immersed in these small groups to help them along. The AI is actually interacting with small groups, listening in on the conversations, analyzing nonverbal behaviors like pointing, and then figuring out how to facilitate those small-group conversations, but always by coordinating with the teacher. The teacher remains the centerpiece here. The AI is providing decision support around the teacher to help them orchestrate their classroom as they see best.

How are students responding to your research?

We know that with AI comes great responsibility. We didn’t want to build anything without first working with the students themselves.

We know that with AI comes great responsibility. We didn’t want to build anything without first working with the students themselves. We organized workshops with them to be transparent, acquire their trust and have their voices heard. However, we soon realized that it was challenging for youth to imagine what good collaboration could look like beyond what they had experienced in school.

So we took a group of students to this cooperative house in Berkeley, Colorado, where they learned how house members had to live together and collaborate outside of schooling. They were introduced to the idea of community agreements, which are mutually agreed upon norms of behavior that the house members themselves co-negotiate and use to hold each other account-able. The youth wondered if an AI could help them to generate and maintain such agreements and developed a design sketch to embody their ideas.

What happened as a result?

This led to one of our AI technologies called the Community Builder (CoBi). With the help of the teacher, students work in small groups to input their examples of agreements into the CoBi interface. As students engage in collaborative learning, CoBi analyzes student discourse for evidence, or “noticings,” of these agreement categories. The results are visualized by way of a growing tree animation that everyone can see, where the noticings are shown as flowers that bloom. Teachers and students use these visualizations to reflect and make sense about their adherence to their agreements.

Now this is where privacy becomes really important. By working with students and getting their sense of comfort, we learned they are terrified of any of their individual talk being known to the teacher. So we do not give the teacher any information on who's speaking and saying what. We don’t even say which student group. It’s all aggregated in this class-level interface, which is the tree.

Are students interacting with the AI interface?

We actually show them what the CoBi is doing, and then the idea is they can correct it if they see something off with its predictions.That gives us good data,and the students can help it improve itself. But more importantly, they can have a conversation about why it’s doing what it’s doing. Because, remember, we also want to teach youth how to learn and collaborate. And so they can have a conversation like, ‘Hey, CoBi, we thought this was an example of being respectful, but you missed it.’

What concerns do you have about ChatGPT right now?

I don’t think we should ban these tools, as that never works. But there's a lot of stuff that still needs to be addressed with these AI programs still. For example, when I’m talking, I’m gesturing and pointing. So I’m making meaning in that context. ChatGPT and all of those other programs are good for their language piece, but they are not grounded in the real world. That’s why we are working with foundational AI to integrate semantics of speech with gesture, gaze and social cues to make an understanding from multimodal, multi-party discourse.

How can teachers quickly be trained in AI?

Right now a phrase that’s used a lot is “responsible AI”.

You can get teachers caught up in AI, and we’re developing curricula for AI literacy for this very purpose. But it’s really a more foundational thing — how can we change learning? How do you design a curriculum that does 21st-century skills, collaboration, critical thinking, inquiry, disciplinary knowledge, experimentation, investigation and developing character at the same time?

You’ve talked a lot about ethical and equitable AI. What does that mean? Right now a phrase that’s used a lot is “responsible AI”. It’s not asking what AI can do, it’s asking what I should do, basically. We have a framework of responsible innovation that we implement in everything we do from the start, and it begins with ourselves — our values, our processes and our commitment to our students and teachers.

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Photo by Patrick Campbell

Sidney D’Mello is a professor in ��ý�Ļ��Ʒ’s Institute of Cognitive Science and Department of Computer Science, and is also director of the National Science Foundation AI Institute for Student-AI Teaming.

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Editor's Note: Fall 2023

Anonymous — Mon, 06 Nov 2023 07:00:00 +0000

Editor's Note: Fall 2023 Anonymous (not verified) Mon, 11/06/2023 - 00:00

Maria Kuntz

In an age of technological advances, progress still hinges on an essential human experience — trust. In a world where artificial intelligence (AI) is evolving at a rapid pace, the poignant ques-tions remain: How should we be using it, and can it be trusted?

Imagining an era without AI is akin to returning to June 28, 2007 — the day before the first iPhone hit the market. New modes of living and working, as well as new challenges, have unfurled since the advent of the now ubiquitous smartphone.

Join us for the ride as we explore the ways CU researchers are studying AI, from classrooms and art studios to cities and highways. Buffs across campus are reshaping the world as we know it.

Did you know ��ý�Ļ��Ʒ ranks fifth nationwide among universities for startup creation? Don’t miss this story and profiles about the Buffs behind Casa Bonita’s revival, Star Trek’s science expert, plus students making an impact in rural Colorado.

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Photo by Misha Photography

In an age of technological advances, progress still hinges on an essential human experience — trust.

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(Art)ificial Intelligence

Anonymous — Mon, 06 Nov 2023 07:00:00 +0000

(Art)ificial Intelligence Anonymous (not verified) Mon, 11/06/2023 - 00:00

Christie Sounart

Artist Hannah Purvis (MFA’25) began using artificial intelligence (AI) programs in her paintings and drawings only last fall. Now, she uses them regularly.

She may upload a rough sketch into a deep learning model like Stable Diffusion to prompt the program to create similar imagery which she’ll then paint by hand, re-upload and create animation frames for interactivity. Other times, she’ll ask AI to purposefully manipulate one of her prints so she can respond to the new image by painting over it.

“This back-and-forth process explores interactive art and uses physical and digital space simultaneously,” said Purvis, who came to CU from Houston, Texas. “In a way, I’m trying to be a computer, and the computer is trying to be a painter.”

Art students at ��ý�Ļ��Ʒ are experiencing a new era firsthand.

“As with the general public, the student population’s response to AI is mixed: Some think of it as just another tool to be used in the creation of new works of art and creative writing,” said CU art and art history professor Mark Amerika, who has worked with AI for four years and integrates it into his teaching. “Others are suspicious of the way AI has appropriated the work of others and prefer to imagine that the only real way to be an artist is to create something supposedly original.”

Amerika — who has his AI-influenced art published in two solo exhibitions this year in Barcelona, Spain and Porto, Portugal — plans to integrate more AI art techniques into the classroom and his creative practice. Students are following suit.

Since 2018, Ryze Xu (MFA’24) has been experimenting with the ways public AI programs use language to produce an output. Then he started using these programs in his art.

As a ceramicist, who turned to clay after eschewing a career path as a fashion designer, he likens his process with AI to using the kiln.

“I view AI as a form of machinery, a tool that, at its core, operates on basic principles akin to all kinds of our daily technology,” said Xu. “The kiln is where we input clay and heat and we end up with fired ceramics, but you can’t see what is happening inside the kiln…With AI we input the world, but we can’t see what’s happening with the AI, and there is unpredictability with this process,” he said.

“I view AI as a form of machinery, a tool that, at its core, operates on basic principles akin to all kinds of our daily technology”

Xu is in favor of embracing AI and has digitized photos of some of his ceramics to train AI programs like Stable Diffusion to produce more art like his.

“I find gratification in comprehending AI’s capabilities and limitations,” said Xu. “This nuanced engagement allows me to offer a different perspective on how we interact with technology and how it influences our artistic expressions.

Eileen Roscina (MFA’23) chooses not to use AI in her work as a filmmaker and multimedia artist.

“It’s very troubling to me,” she said. “So much of it is an illusion — an illusion of connection.”

Roscina uses natural materials in her art, like creating works with pressed flowers. She’s drawn to the ephemeral nature of them, she explained, and the fact that they don’t last.

“Art brings the potential for a deeply human connection,” she said. “I want people to realize the beauty of not recording everything.”

Regardless of their views on AI, all three students agree that it’s too new to make predictions yet.

“We’ve only really been talking about this for a year,” said Purvis. “Just like in art history when the camera was invented and people were really resistant to the change it brought, I think AI can be seen as a new tool in the same way.”

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Art courtesy Hannah Purvis (top); Ryze Xu (middle); Eileen Roscina (bottom)

Some CU MFA students embrace AI programs in their work. Some stay far away.

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Is the World Ready for Self-Driving Cars?

Anonymous — Mon, 06 Nov 2023 07:00:00 +0000

Is the World Ready for Self-Driving Cars? Anonymous (not verified) Mon, 11/06/2023 - 00:00

Daniel Oberhaus

In August, the California Public Utilities Commission made history when it voted to allow two self-driving car companies, Waymo and Cruise, to commercially operate their “robotaxis” around the clock in San Francisco.

Within hours, Cruise reported at least 10 incidents where vehicles stopped short of their destination, blocking city streets. The commission demanded they recall 50% of their fleet.

Despite these challenges, other cities — including Las Vegas, Miami, Austin and Phoenix — are allowing autonomous vehicle startups to conduct tests on public roads.

"Self-driving car proponents see the jump from laboratories to real-world testing as a necessary step that has been a long time coming."

Self-driving car proponents see the jump from laboratories to real-world testing as a necessary step that has been a long time coming. The first autonomous vehicle was tested on the Autobahn in Germany in 1986, but the advances stalled in the 1990s due to technology limitations.

After a 2007 Defense Department’s Advanced Research Projects Agency (DARPA) competition featuring autonomous driving capabilities, it seemed like the era of driverless cars had finally arrived. The competition kickstarted a Silicon Valley race to develop the first commercial driverless car. Optimism abounded, with engineers, investors and automakers predicting there would be as many as 10 million self-driving cars on the road by 2020.

“The question for the last 30 years is — how long is this going to take?” said Javier von Stecher (PhDPhys’08), senior software engineer at Nvidia who has worked on self-driving car technology at companies including Uber and Mercedes-Benz. “I think a lot of people were oversold on the idea that we could get this working fast. The biggest shift I’ve seen over the past decade is people realizing how hard this problem really is.”

The stakes may be high, but that’s not deterring ��ý�Ļ��Ʒ researchers. From creating systems and models to studying human-machine interactions, university teams are working to advance the field safely and responsibly as self-driving cars become a fixture in our society.

Their next big question: Can we learn to trust these vehicles?

Cruise Control

The idea behind autonomous vehicles is simple. An artificial intelligence system pulls in data from an array of sensors including radar, high-resolution cameras and GPS, and uses this data to navigate from point A to point B while avoiding obstacles and obeying traffic laws. Sounds simple? It’s not.

When a self-driving car encounters an unexpected obstacle, it makes split-second judgment calls — should it brake or swerve around it? — that develop naturally in humans but are still beyond even the most sophisticated AI systems.

Moreover, there will always be an edge case that the AI-powered car hasn’t seen before, which means the key to safe autonomous vehicles is building systems that can correctly favor safe choices in unfamiliar situations.

Majid Zamani, associate professor and director of ��ý�Ļ��Ʒ’s Hybrid Systems Control Lab, studies how to create software for autonomous systems such as cars, drones and airplanes. In autonomous vehicles’ AI systems, data flows into the AI and helps it make decisions. But how the AI creates those decisions is a mystery. This, said Zamani, makes it difficult to trust the AI system — and yet trust is critically important in high-stakes applications like autonomous driving.

“These are what we call safety critical applications because system failure can cause loss of life or damage to property, so it’s really important that the way those systems are making decisions is provably correct,” Zamani said.

In contrast to AI systems that use data to create models that are not intelligible to humans, Zamani advocates for a bottom -up approach where the AI’s models are derived from fundamental physical laws, such as acceleration or friction, which are well-understood and unchanging.

“If you derive a model using data, you have to be able to ensure that you can quantify how much error is in that model and the actual system that uses it,” Zamani said.

Mathematically demonstrating the safety of the models used by autonomous vehicles is important for engineers and policymakers who need to guarantee safety before they’re deployed in the real world. But this raises some thorny questions: How safe is “safe enough,” and how can autonomous vehicles communicate these risks to drivers?

Computer, Take the Wheel

Each year, more than 40,000 Americans die in car accidents, and according to the National Highway Traffic Safety Administration (NHTSA), about 90% of U.S. auto deaths and serious crashes are attributable to driver error. The great promise of autonomous vehicles is to make auto deaths a relic of history by eliminating human errors with computers that never get tired or distracted.

The NHTSA designates six levels of “autonomy” for self-driving cars, which range from Level 0 (full driver control) to Level 5 (fully autonomous). For most of us, Level 5 is what we think of when we think of self-driving cars: a vehicle so autonomous that it might not even have a steering wheel and driver’s seat because the computer handles everything. For now, this remains a distant dream, with many automakers pursuing Level 3 or 4 autonomy as stepping stones.

“Most modern cars are Level 2, with partial autonomous driving,” said Chris Heckman, associate professor and director of the Autonomous Robotics and Perception Group in ��ý�Ļ��Ʒ’s computer science department. “Usually that means there’s a human at the wheel, but they can relegate some functions to the car’s software such as automatic braking or adaptive cruise control.”

While these hybrid AI-human systems can improve safety by assisting a driver with braking, acceleration and collision avoidance, limitations remain. Several fatal accidents, for example, have resulted from drivers’ overreliance on autopilot, which stems from issues of human psychology and AI understanding.

Fostering Trust

This problem is deeply familiar to Leanne Hirschfield, associate research professor at the Institute of Cognitive Science and the director of the System-Human Interaction with NIRS and EEG (SHINE) Lab at ��ý�Ļ��Ʒ. Hirschfield’s research focuses on using brain measurements to study the ways humans interact with autonomous systems, like self-driving cars and AI systems deployed in elementary school classrooms.

"When an autonomous vehicle can show the driver information about how it’s making decisions or its level of confidence in its decisions, the driver is better equipped to determine when they need to grab the wheel."

Trust, Hirschfield said, is defined as a willingness to be vulnerable and take on risks, and for decades the dominant engineering paradigm for autonomous systems has been focused on ways to foster total trust in autonomous systems.

“We’re realizing that’s not always the best approach,” Hirschfield said. “Now, we’re looking at trust calibration, where users often trust the system but also have enough information to know when they shouldn’t rely on it.”

The key to trust calibration, she said, is transparency. When an autonomous vehicle can show the driver information about how it’s making decisions or its level of confidence in its decisions, the driver is better equipped to determine when they need to grab the wheel.

Studying user responses is challenging in a laboratory setting, where it’s difficult to expose drivers to real risks. So Hirschfield and researchers at the U.S. Air Force Academy have been using a Tesla modified with a variety of internal sensors to study user trust in autonomous vehicles.

“Part of what we’re trying to do is measure someone’s level of trust, their workload and emotional states while they’re driving,” Hirschfield said. “They’ll have the car whipping around hills, which is how you need to study trust because it involves a sense of true risk compared to a study in a lab setting.”

Although Hirschfield said that researchers have made a lot of progress in understanding how to design autonomous vehicles to foster driver trust, there is still a lot of work to be done.

Human-Centered Design

Sidney D’Mello, a professor at the Institute of Cognitive Science, studies how human-computer interactions shift the way we think and feel. For D’Mello, it’s unclear whether the current crop of self-driving cars can shift to a new driver-focused paradigm from the current perfected engineering-forward approach.

“I think we need an entirely new methodology for the self-driving car context,” D’Mello said. “If you really want something you can trust, then you need to design these systems with users starting from day one. But every single car company is kind of stuck in this engineering mindset from 50 years ago where they build the tech and then they present it to the user.”

The good news, D’Mello said, is that automakers are starting to take this challenge seriously. A collaboration between Toyota and the Institute of Cognitive Science focused on designing autonomous vehicles that foster trust in the user.

“The autonomous model typically implies the AI is in the center with the human hovering around it,” said D’Mello. “But this needs to be a model with the human in the center.”

Even when users learn to trust autonomous vehicles, living with driverless cars and reconceptualizing how they relate to them is complex. But there’s a lot we can apply from research on prosthetics, said Cara Welker, assistant professor in biomechanics, robotics and systems design.

Much like autonomous vehicles analyze surroundings to make navigation and control decisions, robotic prostheses monitor a wearer’s movements to understand appropriate behavior. And just as teaching users to trust prosthetics requires strong feedback loops and predictable prosthetic behavior, teaching drivers to trust autonomous vehicles means providing drivers with information about what the AI is doing — and it requires drivers to reconceptualize vehicles as extensions of themselves.

“There’s a difference between users being able to predict the behavior of an assistive device versus having some kind of sensory feedback,” Welker said. “And this difference has been shown to affect whether the people think of it as ‘me and my prosthesis’ instead of just ‘me, which includes my prosthesis.’ And that’s incredibly important in terms of how users will trust that device.”

How, then, will drivers evolve to experience cars as extensions of themselves?

Next Exit

In 2018, a pedestrian was killed by a self-driving Uber in Arizona, which marked the first fatality attributed to an autonomous vehicle. Although the driver pleaded guilty in the case, the question of who is responsible when autonomous vehicles kill is far from settled.

Today, there is limited regulation dictating autonomous vehicle safety and liability. One problem is that vehicles are regulated at the federal level while drivers are regulated at the state level — a division of responsibility that doesn’t account for a future where the driver and vehicle are more closely aligned.

Researchers and automakers have voiced frustration with existing autonomous driving regulations, agreeing that updated regulations are necessary. Ideally, regulations would ensure driver, passenger and pedestrian safety without quashing innovation. But what these policies might look like is still unclear.

The challenge, said Heckman, is that the engineers don’t have complete control over how autonomous systems behave in every circumstance. He believes it’s critical for regulations to account for this without insisting on impossibly high safety standards.

“Many of us work in this field because automotive deaths seem avoidable and we want to build technologies that solve that problem,” Heckman said. “But I think we hold these systems [to] too high of a standard — because yes, we want to have safe systems, but right now we have no safety frameworks, and automakers aren’t comfortable building these systems because they may be held to an extremely high liability.”

Other industries may offer a vision for how to regulate the autonomous driving industry while providing acceptable safety standards and enabling technological development, Heckman said. The aviation industry, for example, adopted rigorous engineering standards and fostered trust in engineers, pilots, passengers and policymakers.

“There’s an engineering principle that trust is a perception of humans,” Heckman said. “Trust is usually built through experience with a system, and that experience confers trust on the engineering paradigms that build safe systems.

“With airplanes, it took decades for us to come up with designs and engineering paradigms that we feel comfortable with. I think we’ll see the same in autonomous vehicles, and regulation will follow once we’ve really defined what it means for them to be trustworthy.”

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Autonomous vehicles are hitting the road in cities across the U.S. Can they be trusted? ��ý�Ļ��Ʒ researchers and alumni weigh in.

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