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Smart Farming and Governing AI in East Africa: Taking Gendered Relations and Vegetal Beings into Account

Jeremy de BeerLaura FosterChidi OguamanamKatie Szilagyi, and Angeline Wairegi will present their paper, Smart Farming and Governing AI in East Africa: Taking Gendered Relations and Vegetal Beings into Account, on Friday, September 24th at #werobot 2021. Edward Tunstel will moderate the 1:45pm – 3:15pm panel on Field Robotics.

Laura Foster


Robots are on their way to East African farms. Deploying robotic farm workers and corresponding smart systems is lauded as the solution for improving crop yields, strengthening food security, generating GDP growth, and combating poverty. These optimistic narratives mimic those of the Green Revolution and activate memories of its underperformance in Africa. Expanding upon previous contributions on smart farming and the colonial aspects of AI technology, this paper investigates how AI-related technologies are deployed across East Africa.

Edward Tunstel (moderator)

Chidi Oguamanam


The creation of AI algorithms and datasets are processes driven by human judgements; the resultant technology is shaped by society. Cognizant of this, this paper provides an overview of emerging smart farming technologies across the East African region, situated within contemporary agricultural industries and the colonial legacies that inform women’s lives in the region.

Angeline Wairegi


After establishing the gendered implications of smart farming as a central concern, this paper provides rich analysis of the state-of-the-art scholarly and policy literature on smart farming in the region, as well as key intergovernmental agricultural AI initiatives being led by national governments, the United Nations, the African Union, and other agencies. This enables an understanding of how smart farming is being articulated across multiple material-discursive sites—media, government, civil society, and industry.

Katie Szilagyi

What becomes apparent is that smart farming technologies are being articulated through four key assumptions: not only techno-optimism, as above, but also ahistoricism, ownership, and human exceptionalism. These assumptions, and the multiple tensions they reveal, limit possibilities for governing smart farming to benefit small-scale women farmers. Using these four frames, our interdisciplinary author team identifies the key ethical implications for adopting AI technologies for East African female farmers.

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Being “Seen” vs. “Mis-seen”: Tensions Between Privacy and Fairness in Computer Vision

Alice Xiang

Alice Xiang will present her paper, Being “Seen” vs. “Mis-seen”: Tensions Between Privacy and Fairness in Computer Vision, on Friday, September 24th at 11:30am at #werobot 2021. Daniel Susser will lead the discussion.

The rise of AI technologies has caused growing anxiety that AI may create mass surveillance systems and entrench societal biases. Major facial recognition systems are less accurate for women and individuals with darker skin tones due to a lack of diversity in the training datasets. Efforts to diversify datasets can raise privacy issues; plaintiffs can argue that they had not consented to having their images used in facial recognition training datasets.

This highlights the tension that AI technologies create between representation vs. surveillance: we want AI to “see” and “recognize” us, but we are uncomfortable with the idea of AI having access to personal data about us. This tension is further amplified when the need for sensitive attribute data to detect or mitigate bias is considered. Existing privacy law addresses this area primarily by erring on the side of hiding people’s sensitive attributes unless there is explicit informed consent. While some have argued that not being “seen” by AI is preferable—that being under-represented in training data might allow one to evade mass surveillance—incomplete datasets may result in detrimental false-positive identification. Thus, not being “seen” by AI does not protect against being “mis-seen.”

Daniel Susser (discussant)

The first contribution of this article is to characterize this tension between privacy and fairness in the context of algorithmic bias mitigation. In particular, this article argues that the irreducible paradox underlying current efforts to design less biased algorithms is the simultaneous desire to be both “seen” yet “unseen” by AI. Second, the Article reviews the viability of strategies that have been proposed for addressing the tension between privacy and fairness and evaluates whether they adequately address associated technical, operational, legal, and ethical challenges. Finally, this article argues that solving the tension between representation and surveillance requires considering the importance of not being “mis-seen” by AI rather than simply being “unseen.” Untethering these concepts (being seen, unseen, vs. mis-seen) can bring greater clarity around what rights relevant laws and policies should seek to protect. Given that privacy and fairness are both critical objectives for ethical AI, it is vital to address this tension head-on. Approaches that rely purely on visibility or invisibility will likely fail to achieve either objective.

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The Legal Construction of Black Boxes

Elizabeth Kumar

Elizabeth KumarAndrew Selbst, and Suresh Venkatasubramanian will present their paper, The Legal Construction of Black Boxes, on Saturday, September 25th at 10:00am at #werobot 2021. Ryan Calo will lead the discussion.

Abstraction is a fundamental technique in computer science. Formal abstraction treats a system as defined entirely by its inputs, outputs, and the relationship that transforms inputs to outputs. If a system’s user knows those details, they need not know anything else about how the system works; the internal elements can be hidden from them in a “black box.” Abstraction also entails abstraction choices: What are the relevant inputs and outputs? What properties should the transformation between them have? What constitutes the “abstraction boundary?” These choices are necessary, but they have implications for legal proceedings that involve the use of machine learning (ML).

Andrew Selbst

This paper makes two arguments about abstraction in ML and legal proceedings. The first is that abstraction choices that can be treated as normative and epistemic claims made by developers that compete with judgments properly belonging to courts. Abstraction constitutes a claim as to the division of responsibility: what is inside the black box is the province of the developer; what is outside belongs to the user. Abstraction also is a factual definition, rendering the system an intelligible and interrogable object. Yet the abstraction that defines the boundary of a system is itself a design choice. When courts treat technology as a black box with a fixed outer boundary, they unwittingly abdicate their responsibility to make normative judgments as to the division of responsibility for certain wrongs, and abdicate part of their factfinding roles by taking the abstraction boundaries as a given. We demonstrate these effects in discussions of foreseeability in tort law, liability in discrimination law, and evidentiary burdens more broadly.

Suresh Venkatasubramanian

Our second argument builds from that observation. By interpreting the abstraction as one of many possible design choices, rather than a simple fact, courts can surface those choices as evidence to draw new lines of responsibility without necessarily interrogating the interior of the black box itself. Courts may draw on evidence about the system as presented to support these alternative lines of responsibility, but by analyzing the construction of the implied abstraction boundary of a system, they can also consider the context around its development and deployment.

Ryan Calo

Courts can rely on experts to compare a designer’s choices with emerging standard practices in the field of ML or assign a burden to a user to justify their use of off-the-shelf technology. After resurfacing the normative and epistemic contentions embedded in the technology, courts can use familiar lines of reasoning to assign liability as proper.

 

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We Robot 2021 Preliminary Program

Join us in person virtually for the 10th Anniversary Edition – Register Here
All times are US Eastern time.

NOTE: Check the Program page for up-to-date information.

Thurs. Sept. 23 Workshop ScheduleWhatWho
10:30-11:00Please see the Attendee Whova Instructions for info about how conference software works and how to log in.Email Ryan Erickson for tech support logging in.
11:00-12:00Here Be Robots:
The panel will discuss basic technical concepts underpinning the latest developments in AI and robotics.
Bill Smart
Cindy Grimm
12:00-1:00LunchEveryone!
1:00-2:00if(goingToTurnEvil), {don’t();}: Creating Legal Rules for Robots
A lawyer, a roboticist, and a sociologist (or other discipline) walk into a bar…to form multidisciplinary teams attempting to craft or tear apart hypothetical legislation. This experiential session combines law, robotics, drones, and networking.
Evan Selinger
Kristen Thomasen
Woody Hartzog
2:00-3:00Break & Breakouts
Finding your Path, Your People, and Your Conference Program--Networking Break
Take a break, or join one of the following networking sessions:
1. How to do interdisciplinary research in this space
2. What do I want to be when I grow up?
3. Welcome to We Robot for newbies
Ryan Calo
Sue Glueck
Kristen Thomasen
3:00-4:00Why Call Them Robots? 100 Years of R.U.R.
The panel will discuss multidisciplinary perspectives on R.U.R., the 1920 sci-fi play by the Czech writer Karel Čapek. "R.U.R." stands for Rossumovi Univerzální Roboti.
Robin Murphy, Joanne Pransky and Jeremy Brett
4:00-4:15BreakEveryone!
4:15-5:30I’ll Take Robot Geeks for $1000, Alex: An Afternoon of Robot Trivia
Light appetizers and beverages will be provided.
Jason Millar
Woody Hartzog

 

Friday, Sept. 24 ScheduleDay One EventsDiscussant
8:30-9:30Check-in / Registration
Please see the Attendee Whova Instructions for info about how conference software works.
Email Ryan Erickson for tech support logging in.
9:30-10:00Welcome and Introductions
10:00-11:00The Legal Construction of Black Boxes
Elizabeth Kumar, Andrew Selbst, and Suresh Venkatasubramanian
Ryan Calo
11:00-11:30Break
Live Demo Q&A
Societal Implications of Large Language Models
Miles Brundage
We suggest viewing recorded demo in advance of Q&A
11:30-12:30Being "Seen" vs. "Mis-seen": Tensions Between Privacy and Fairness in Computer Vision
Alice Xiang
Daniel Susser
12:30-12:45Lightning Poster Session & Announcements
12:45-1:45Lunch Break
1:45-3:15Field Robotics Panel
Moderator: Edward Tunstel
3:15-3:45Break
Live Demo Q&A
Skills from Students – Artifacts from a Robot Interaction Design Curriculum for Fifth Grade Students
Daniella DiPaola
We suggest viewing recorded demo in advance of Q&A
3:45-4:45Social Robots and Children’s Fundamental Rights: A Dynamic Four-Component Framework for Research, Development, and Deployment
Vicky Charisi, Selma Šabanović, Urs Gasser, and Randy Gomez
Veronica Ahumada-Newhart
4:45-5:15Break
Live Demo Q&A: Robots and Robotics as a service. Service Robots you can use today.
Jean Duteau, CEO of Robot World
We suggest viewing recorded demo in advance of Q&A
5:15-6:15Driving Into the Loop: Mapping Automation Bias & Liability Issues for Advanced Driver Assistance Systems
Katie Szilagyi, Jason Millar, Ajung Moon, and Shalaleh Rismani
Meg Leta Jones
6:15-7:15Poster Session & Reception

7:45-9:45Conference DinnerVirtual....

 

Saturday Sept. 25 ScheduleDay Two EventsDiscussant
9:00-10:00Registration
Please see the Attendee Whova Instructions for info about how conference software works.
Email Ryan Erickson for tech support logging in.
10:00-11:00Debunking Robot Rights: Metaphysically, Ethically and Legally
Abeba Birhane, Jelle van Dijk, and Frank Pasquale
Deb Raji
11:00-11:30Break
Live Demo Q&A
Skills from Students – Artifacts from a Robot Interaction Design Curriculum for Fifth Grade Students
Daniella DiPaola
We suggest viewing recorded demo in advance of Q&A
11:30-12:30Autonomous Vehicle Fleets as Public Infrastructure
Thomas Gilbert and Roel Dobbe
Madeleine Clare Elish
12:30-1:30Lunch Break
1:30-2:30Predicting Consumer Contracts
Noam Kolt
Meg Mitchell
2:30-3:00Break
Live Demo Q&A
Societal Implications of Large Language Models
Miles Brundage
We suggest viewing recorded demo in advance of Q&A
3:00-4:00Anti-Discrimination Law’s Cybernetic Black Hole
Marc Canellas
Cynthia Khoo
4:00-4:30Break
4:30-5:30Health Robotics Panel
Moderator: Michelle Johnson
5:30-5:45Awards of Prizes for Best Poster, Best Paper (Jr. Scholars), Best Paper (Sr. Scholars)
Summary & Conclusion
Announcement of next We Robot
Kate Darling
Michael Froomkin

Demos

Societal Implications of Large Language Models
Miles Brundage

Skills from Students – Artifacts from a Robot Interaction Design Curriculum for Fifth Grade Students
Daniella DiPaola

We also plan some surprises!

Note: For the latest updates keep an eye on the We Robot 2021 Program page

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We Robot 2021 Will Have Terrific Papers & Demos

We Robot 2021 is proud to announce the list of accepted papers for our September 24 & 25 meeting days (the 23rd will be our Workshop day – details soon). These papers survived a rigorous double-blind review process, and represent less than 15% of the submissions we received. Sadly, many very good papers got turned away. Happily, we can look forward to these:

Debunking Robot Rights: Metaphysically, Ethically and Legally
Abeba Birhane, Jelle van Dijk, and Frank Pasquale

Discrimination as a Cybernetic System Accident
Marc Canellas

Social Robots and Children’s Fundamental Rights: A Dynamic Four-Component Framework for Research, Development, and Policy
Vicky Charisi, Urs Gasser, Randy Gomez, and Selma Šabanović

Autonomous Vehicles as Public Infrastructure: Building an “AV Development Index” for Tomorrow’s Cities
Roel Dobbe and Thomas Gilbert

Bias in Contract Prediction: A Case Study of GPT-3
Noam Kolt

The Legal Construction of Black Boxes: How Machine Learning Practice Informs Foreseeability
I. Elizabeth Kumar, Andrew Selbst, and Suresh Venkatasubramanian

Driving Into the Loop: Mapping Automation Bias & Liability Issues for Advanced Driver Assistance Systems
Jason Millar, Ajung Moon, Shalaleh Rismani, and Katie Szilagyi

Being “Seen” vs. “Unseen”: Tensions Between Privacy and Fairness in Algorithmic Bias Mitigation
Alice Xiang

Field Robotics Panel

  • Robots in the Ocean, Annie Brett
  • Smart Farming versus Traditional Knowledge: Mapping the Impacts of AI Automation on East African Smallholder Female Farmers, Jeremy de Beer, Laura Foster, Chidi Oguamanam, Katie Szilagyi, and Angeline Wairegi
  • On the Practicalities of Robots in Public Spaces, Cindy Grimm, Bill Smart, and Kristen Thomasen

Health Panel

  • Somebody That I Used to Know: The Risks of Personalizing Robots for Dementia Care, Sharon Banh, Soyon Kim, Alyssa Kubota, Maryam Pourebadi, and Laurel D. Riek
  • Diverse Patient Perspectives on the Role of AI and Big Data in Healthcare, Kelly Bergstrand, Jess Findley, Christopher Robertson, Marv Slepian, and Andrew Woods
  • Prescribing Discrimination, Krista Kennedy and Charlotte Tschider

Demos

Societal Implications of Large Language Models
Miles Brundage

Skills from Students – Artifacts from a Robot Interaction Design Curriculum for Fifth Grade Students
Daniella Ditaola

 

Please note that we are accepting proposals for posters on a rolling basis until June 1.

We anticipate announcing the form of the conference — in person, virtual, or blended — in early July, so watch this space.  We will also announce a tentative program schedule once we sort out a few logistics…

 

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We Robot Paper Submission Deadline Extended One Week

Everyone says it’s harder to get things done under COVID, so we’re extending the deadline for submission of paper abstracts to We Robot 2021 by one week – to midnight US East Coast time on February 8, 2021.

We will attempt to keep to the rest of the schedule, but paper acceptance notices may end up slightly delayed also.

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