Human-AI Systems for Visual Information Access with Anhong Guo (hosted by Seongkook Heo)
March 3, 2020, 11:00am in the Link Lab Arena, 2nd floor Olsson Hall, UVA
Anhong Guo creates hybrid human- and AI-powered intelligent interactive systems to provide access to visual information in the real world. By combining the advantages of humans and AI, these systems can be nearly as robust and flexible as humans, and nearly as quick and low-cost as automated AI, enabling us to solve problems that are currently impossible with either alone.
He developed and deployed human-AI systems for two application domains: accessibility and environmental sensing. To make physical interfaces accessible for blind people, Guo developed systems to interpret static and dynamic interfaces, enabling blind people to independently access them through audio feedback or tactile overlays. For environmental sensing, he developed and deployed a camera sensing system that collects human labels to bootstrap automatic processes to answer real-world visual questions, allowing end users to actionalize AI in their everyday lives.
AI systems often a require huge amount of up front training data to get started, but targeted human intelligence can bootstrap the systems with relatively little data. Although humans may be slower initially, quickly bootstrapping to automated approaches provides a good balance, enabling human-AI systems to be scalable and rapidly deployable.
About the speaker:
Anhong Guo is a Ph.D. candidate in the Human-Computer Interaction Institute in the School of Computer Science at Carnegie Mellon University, advised by Dr. Jeffrey Bigham. He is also a Snap Inc. Research Fellow, and a Swartz Innovation Fellow for Entrepreneurship. He has published in many top academic conferences in interface technologies, wearable computing, accessibility and computer vision, including two best paper nominees. Before CMU, he received his Master’s in HCI from Georgia Tech. He has also worked in the Ability and Intelligent User Experiences groups in Microsoft Research, the HCI group of Snap Research, the Accessibility Engineering team at Google, and the Mobile Innovation Center of SAP America. He is a candidate for a Tenure Track Faculty position in the Department of Computer Science.
Friday and Saturday, March 20 (Newcomb Hall South Meeting Room – 21 (Rotunda Dome Room)
Hear from researchers studying Big Data about how they respond to the question of how algorithmic systems support emergent understandings of “the human,” “the social,” and conceptions of “the ethical.” This workshop will engage pressing questions of data ethics by critically assessing large-scale information systems and forms of algorithmic reasoning. The conference explores large-scale data analytics with respect to the ways in which they support specific ways of being in the world, forms of perception and intervention, and forms of knowing, while preventing other modes of life from flourishing. How does openness for new ethical projects persist in algorithmic systems? How might predictive analytics foreclose the possibility of alternative futures? What, in other words, are the ethics and politics of openness and closure in contemporary algorithmically-mediated conditions? In light of the current proliferation of dystopian visions of algorithmic futures with ubiquitous digital surveillance and control, what alternative futures could be brought about in and through computational infrastructures to be designed and implemented otherwise?
March 27, 2020, 9:00am to 5:00pm in Alumni Hall
WiDS Charlottesville is an independent event organized by the UVA School of Data Science to coincide with the annual Global Women in Data Science (WiDS) Conference held at Stanford University and an estimated 150+ locations worldwide. All genders are invited to attend WiDS regional events, which feature outstanding women doing outstanding work. This year’s conference features dynamic keynote presentations with industry and academic experts in artificial intelligence, skills sessions, research lightening talks, a panel with senior women in data science, and more.
April 17-18, 2020, Schwarzman College of Computing, Cambridge, MA
MIT Schwarzman College of Computing and the Jain Family Institute announce a call for abstracts for a workshop on the ethics of algorithmic decision-making systems (ADS). They invite abstracts from all academic disciplines, including (but not limited to) philosophy, computer science, history, political science, anthropology, law, gender studies, criminology, sociology, and data science.
Topics may include:
- Explainability: What counts as an explanation of an algorithmic
decision? Of a decision system? Will a single kind of explanation suffice,
or will there be different types of explanation required by different
contexts (legal proceedings, credit scoring, or university admissions)? How
can work on explanation by philosophers of science, ethicists, and
philosophers of law shed light on these questions?
- Governance: What kinds of institutional structures should be in place
for the administration and oversight of ADS?
- Fairness: To what extent, and how, should considerations about bias,
discrimination, and fairness factor into the design of ADS?
- Autonomy and Manipulation: Does the increasingly pervasive use of ADS
by both governments and private entities raise distinctive concerns about
autonomy, democratic accountability, and due process? What protections
should be in place to protect citizens from manipulation by ADS?
To apply, send an anonymized abstract of no more than three double-spaced
pages to firstname.lastname@example.org by March 1st, 2020.
If your abstract is selected for the workshop, you will be asked to provide a draft of your paper for circulation to attendees by April 1st, 2020. They expect to cover travel and lodging expenses for all speakers. Participation in the workshop will be limited to invited guests and speakers only.