The Academic Fringe Festival
First edition on
First edition on
Crowd Computing & Human-Centered AI
Crowd Computing & Human-Centered AI
The Academic Fringe Festival is an exciting concoction of invited talks and panel discussions around important themes of research and innovation in Computer Science. This first edition is on "Crowd Computing and Human-Centered AI". The series features prominent researchers and practitioners, whose work has made fundamental contributions in these fields.
The Academic Fringe Festival is an exciting concoction of invited talks and panel discussions around important themes of research and innovation in Computer Science. This first edition is on "Crowd Computing and Human-Centered AI". The series features prominent researchers and practitioners, whose work has made fundamental contributions in these fields.
Calling this collection of academic events "The Academic Fringe Festival" is an ode to the story of the eight theatre companies which turned up uninvited at the Edinburgh International Festival in 1947 and performed on the fringe of the event. Over the years, such acts gained popularity and gradually snowballed into what is now the world's largest arts festival, the "Edinburgh Fringe Festival". Our aim is not to create the world's largest academic festival, but to create a forum for open, accessible, and inspiring dissemination of knowledge from renowned scientists across the globe.
Calling this collection of academic events "The Academic Fringe Festival" is an ode to the story of the eight theatre companies which turned up uninvited at the Edinburgh International Festival in 1947 and performed on the fringe of the event. Over the years, such acts gained popularity and gradually snowballed into what is now the world's largest arts festival, the "Edinburgh Fringe Festival". Our aim is not to create the world's largest academic festival, but to create a forum for open, accessible, and inspiring dissemination of knowledge from renowned scientists across the globe.
The Academic Fringe Festival is free of cost and open to everyone who is interested to participate. Let there be light!
The unprecedented rise in the adoption of artificial intelligence techniques in many contexts is concomitant with shortcomings of such technology with respect to robustness, interpretability, usability, and trustworthiness. Crowd computing offers a viable means to engage a large number of human participants in data related tasks and in user studies. In the context of overcoming the computational and interactional challenges facing the current generation of AI systems, recent work has shown how crowd computing can be leveraged to either debug noisy training data in machine learning systems, understand which machine learning models are more congruent to human understanding in particular tasks, or to advance our understanding of how AI systems can influence human behavior.
The unprecedented rise in the adoption of artificial intelligence techniques in many contexts is concomitant with shortcomings of such technology with respect to robustness, interpretability, usability, and trustworthiness. Crowd computing offers a viable means to engage a large number of human participants in data related tasks and in user studies. In the context of overcoming the computational and interactional challenges facing the current generation of AI systems, recent work has shown how crowd computing can be leveraged to either debug noisy training data in machine learning systems, understand which machine learning models are more congruent to human understanding in particular tasks, or to advance our understanding of how AI systems can influence human behavior.
The Speakers
The Speakers
Matthew Lease
Matthew Lease
Adventures in Crowdsourcing: Toward Safer Content Moderation and Better Supporting Complex Annotation Tasks [more details]
Adventures in Crowdsourcing: Toward Safer Content Moderation and Better Supporting Complex Annotation Tasks [more details]
University of Texas at Austin, Amazon Scholar
Gianluca Demartini
Gianluca Demartini
Bias in Human-in-the-loop Artificial Intelligence [more details]
Bias in Human-in-the-loop Artificial Intelligence [more details]
University of Queensland
Shamsi Iqbal
Shamsi Iqbal
Redefining Productivity to Adapt to a Changing Landscape of Work [more details]
Redefining Productivity to Adapt to a Changing Landscape of Work [more details]
Microsoft
Panos Ipeirotis
Panos Ipeirotis
Demand-Aware Career Path Recommendations: A Reinforcement Learning Approach [more details]
Demand-Aware Career Path Recommendations: A Reinforcement Learning Approach [more details]
New York University
Olga Megorskaya
Olga Megorskaya
Variety of crowdsourcing implementations: ML and business applications [more details]
Variety of crowdsourcing implementations: ML and business applications [more details]
Toloka
Edith Law
Edith Law
Crowdsourcing Medical Time Series Annotation: Expertise, Ambiguity and Human-AI Collaboration [more details]
Crowdsourcing Medical Time Series Annotation: Expertise, Ambiguity and Human-AI Collaboration [more details]
University of Waterloo
More speakers coming soon...
More speakers coming soon...
If you are interested in participating as a 'Speaker' or a 'Panelist' in either this edition of TAFF or an upcoming edition in the future, please reach out to Dr. Ujwal Gadiraju.
Schedule
Schedule