Advancing Explainability Through AI Literacy And Design Resources
Allison Woodruff
ACM Distinguished Speaker
Google
02/19/2024
Explainability helps people understand and interact with the systems that make decisions and inferences about them. This should go beyond providing explanations at the moment of a decision; rather, explainability is best served when information about AI is incorporated into the entire user journey and AI literacy is built continuously throughout a person's life. We share resources that can be used in both industrial and academic environments to encourage AI practitioners to think more broadly about what explanations can look like across products and ways to provide people with a solid foundation that helps them better understand AI systems and decisions.
Robots that Need to Mislead: Biologically-inspired Machine Deception
Ronald Arkin
IEEE Distinguished Speaker, Professor Emeritus
Georgia Institute of Technology
02/26/2024
Expanding our work in understanding the relationships maintained in teams of humans and robots, this talk describes research on deception and its application within robotic systems. Earlier we explored the use of psychology as the basis for producing deceit in robotic systems in order to evade capture. More recent work involves studying squirrel hoarding and bird mobbing behavior as it applies to deception, in the first case for misleading a predator, and in the second for feigning strength when none exists. Next, we discuss other-deception, where deceit is performed for the benefit of the mark. Finally, newly completed research on team deception where groups of agents using shills that serve to mislead others is presented. Results are presented in both simulation and simple robotic systems, as well as consideration of the ethical implications of this research.
From Theory to Practice: How Computer Science Forms a Foundation for Software Engineering
Brandon Hoshi ('19)
Software Engineer
Visual Concepts
03/04/2024
For most, the reason for obtaining a computer science degree is to ultimately pursue a career as a software engineer. While there is inevitably a great deal of programming involved in a computer science program, students may still end up anxious about whether what they’re learning is actually useful or not. In this talk I will explain that the answer is an unequivocal “Yes”. The foundational knowledge created through studying computer science is invaluable in a career as a software engineer. Through personal examples from working as an engineer at a AAA game developer, I will show how theoretical knowledge translates to concrete skills and shine a spotlight on parts of computer science that are significantly more important than most students might realize. I will also talk about important skills for software engineers that aren’t directly related to computer science.
Data Science At Scale Everywhere for Everyone
Doris Lee
ACM Distinguished Speaker
CEO and co-founder of Ponder
03/11/2024
Over the past decade, the democratization of data science tooling, particularly through Python libraries like pandas and NumPy, has empowered practitioners of all levels to work with data efficiently. Yet, despite the popularity of these tools, they present challenges as practitioners look to scale their workflows to production. In this talk, we explore the limitations of these tools and pain points that data scientists encounter when dealing with data at scale. Next, I will share how we are solving this problem at Ponder, with both our open-source project Modin and our groundbreaking technology that lets anyone run their Python data workflows directly in their databases.
Searching for Justice in Programming Language Design
Amy J. Ko
ACM Distinguished Speaker, Professor
University of Washington
03/25/2024
From its earliest days, computing has been an eclectic project of capitalism, war, colonialism, and white supremacy. Its central Western values of utility, efficiency, rationality, and mathematical beauty have enabled sweeping changes to culture and communication, but also amplified some of the worst parts of these oppressive systems. At the heart of many of these forces are programming languages, which deeply embed many assumptions about their users: English fluency, normative ability, and a devotion to speed. These assumptions create a culture of computing that structurally excludes vast parts of humanity from participating. In this talk, I describe some of my nascent efforts to design the opposite: programming language that seeks to be global, accessible, playful, and simple, embracing all of humanity’s natural languages and abilities, while trading computing’s devotion to efficiency for simplicity and silliness. Throughout, I’ll provide demonstrations of these gestures toward programming language justice, pointing to alternative visions for how we might make with computing and who might do the making.