Invited Talks |
Invited Talks - HAI 19
Invited Talks in the workshop are being organized across a diverse set of topics and by some renowned researchers, details are mentioned below.
Pascale Fung
Talk Title: Towards a More Gender Equal World using AI
Abstract:
Language representations from language models to word embeddings are known to reflect gender bias, where "doctor" is more closely associated with men and "nurse" with women. Intelligent system performances, ranging from that of voice recognition to recruitment tools, are known to favor male users. Virtual assistants such as Alexa, and humanoid robots such as Sophia, are often in female form whereas robots that perform physical tasks are often in male form. These gender roles of AI and robotics systems mirror the gender roles in the physical world, where deep seated bias, at times unconscious, has led to the acceptance of such roles. The cultural influence of science fiction and the gender roles of AI and robots in this genre are also non-negligible. Historical data also shows that the creators of both fictional and non-fictional AI and robot systems are predominantly men. Do NLP algorithms exacerbate gender bias or can they be used to mitigate such bias?
In this talk, I will describe our work in detecting gender bias in both traditional media and social media. I will also describe my experience and insight with gender roles in AI in my research career, where I started from working on the world's first continuous speech recognizer, to creating virtual assistants and conversational systems. I hope to share with the audience that, at the cusp of the 4th Industrial Revolution, the need for creating a more gender balanced world of AI has never been so urgent. I will also propose some achievable goals for the AI research community.
Talk Title: Towards a More Gender Equal World using AI
Abstract:
Language representations from language models to word embeddings are known to reflect gender bias, where "doctor" is more closely associated with men and "nurse" with women. Intelligent system performances, ranging from that of voice recognition to recruitment tools, are known to favor male users. Virtual assistants such as Alexa, and humanoid robots such as Sophia, are often in female form whereas robots that perform physical tasks are often in male form. These gender roles of AI and robotics systems mirror the gender roles in the physical world, where deep seated bias, at times unconscious, has led to the acceptance of such roles. The cultural influence of science fiction and the gender roles of AI and robots in this genre are also non-negligible. Historical data also shows that the creators of both fictional and non-fictional AI and robot systems are predominantly men. Do NLP algorithms exacerbate gender bias or can they be used to mitigate such bias?
In this talk, I will describe our work in detecting gender bias in both traditional media and social media. I will also describe my experience and insight with gender roles in AI in my research career, where I started from working on the world's first continuous speech recognizer, to creating virtual assistants and conversational systems. I hope to share with the audience that, at the cusp of the 4th Industrial Revolution, the need for creating a more gender balanced world of AI has never been so urgent. I will also propose some achievable goals for the AI research community.
Daniel McDuff
Talk Title: Building Intelligent and Visceral Machines: From Sensing to Synthesis
Abstract:
Humans have evolved to have highly adaptive behaviors that help us survive and thrive. AI can help us advance the fundamental understanding of human behavior and emotions, build smarter technology, and ultimately help people. In this talk, I will present novel methods for physiological and behavioral measurement via ubiquitous hardware. Then I will present state-of-the-art approaches for emotion synthesis that can be used to create rich human-agent interactions. Finally, I will show examples of new human-computer interfaces and autonomous systems that leverage behavioral and physiological signals, including emotion-aware natural language conversation systems, cross-domain learning systems and vehicles with intrinsic emotional drives. This technology presents many opportunities for building natural user interfaces and more intelligent machines; however, it also raises questions about the ethics of designing emotionally-aware artificial systems. Throughout the talk I will comment on many of these questions and propose design principals to help address them.
Talk Title: Building Intelligent and Visceral Machines: From Sensing to Synthesis
Abstract:
Humans have evolved to have highly adaptive behaviors that help us survive and thrive. AI can help us advance the fundamental understanding of human behavior and emotions, build smarter technology, and ultimately help people. In this talk, I will present novel methods for physiological and behavioral measurement via ubiquitous hardware. Then I will present state-of-the-art approaches for emotion synthesis that can be used to create rich human-agent interactions. Finally, I will show examples of new human-computer interfaces and autonomous systems that leverage behavioral and physiological signals, including emotion-aware natural language conversation systems, cross-domain learning systems and vehicles with intrinsic emotional drives. This technology presents many opportunities for building natural user interfaces and more intelligent machines; however, it also raises questions about the ethics of designing emotionally-aware artificial systems. Throughout the talk I will comment on many of these questions and propose design principals to help address them.
Rui Yan
Talk Title: Recent Advances and Challenges on Human-Computer Conversational Systems
Abstract:
Nowadays, automatic human-computer conversational systems have attracted great attention from both industry and academia. Intelligent products such as XiaoIce have been released, while tons of Artificial Intelligence companies have been established. We see that the technology behind the conversational systems is accumulating and now open to the public gradually. With the investigation of researchers, conversational systems are more than scientific fictions: they become real. It would be interesting to review the recent development of human-computer conversational systems, especially the significant changes brought by deep learning techniques.
Talk Title: Recent Advances and Challenges on Human-Computer Conversational Systems
Abstract:
Nowadays, automatic human-computer conversational systems have attracted great attention from both industry and academia. Intelligent products such as XiaoIce have been released, while tons of Artificial Intelligence companies have been established. We see that the technology behind the conversational systems is accumulating and now open to the public gradually. With the investigation of researchers, conversational systems are more than scientific fictions: they become real. It would be interesting to review the recent development of human-computer conversational systems, especially the significant changes brought by deep learning techniques.
Virginia Dignum
Talk Title: Responsible AI
Abstract:
As Artificial Intelligence (AI) systems are increasingly making decisions that directly affect users and society, many questions raise across social, economic, political, technological, legal, ethical and philosophical issues. Can machines make moral decisions? How should moral, societal and legal values be part of the design process? In this talk, I look at ways to ensure that behavior by artificial systems is aligned with human values and ethical principles. Given that ethics are dependent on the socio-cultural context and are often only implicit in deliberation processes, methodologies are needed to elicit the values held by designers and stakeholders, and to make these explicit leading to better understanding and trust on artificial autonomous systems. We will in particular focus on the ART principles for AI: Accountability, Responsibility, Transparency.
Talk Title: Responsible AI
Abstract:
As Artificial Intelligence (AI) systems are increasingly making decisions that directly affect users and society, many questions raise across social, economic, political, technological, legal, ethical and philosophical issues. Can machines make moral decisions? How should moral, societal and legal values be part of the design process? In this talk, I look at ways to ensure that behavior by artificial systems is aligned with human values and ethical principles. Given that ethics are dependent on the socio-cultural context and are often only implicit in deliberation processes, methodologies are needed to elicit the values held by designers and stakeholders, and to make these explicit leading to better understanding and trust on artificial autonomous systems. We will in particular focus on the ART principles for AI: Accountability, Responsibility, Transparency.
Rafal Rzepka
Talk Title: Humanizing Machines by Simulating Empathy and Understanding Human Needs
Abstract:
In my talk, I will introduce my work on utilizing the wisdom of crowds in various tasks aiming at natural and safe machine behavior. By presenting examples from my group's work on humor, dialog, and poetry generation, I will underline the necessity of emotional and moral common sense in the process of applying these algorithms to real-life applications.
The core question I want to pose is how empathy, the critical component of our choices and decisions, can be simulated. To illustrate my approach, I will present our experiments with a vacuum-cleaning robot that tries to predict a user's intentions and its capabilities to infer if help is needed. I will conclude my talk with listing problems related to over-humanizing AI in order to spark a discussion about boundaries and limitations of too-human-like machines.
Talk Title: Humanizing Machines by Simulating Empathy and Understanding Human Needs
Abstract:
In my talk, I will introduce my work on utilizing the wisdom of crowds in various tasks aiming at natural and safe machine behavior. By presenting examples from my group's work on humor, dialog, and poetry generation, I will underline the necessity of emotional and moral common sense in the process of applying these algorithms to real-life applications.
The core question I want to pose is how empathy, the critical component of our choices and decisions, can be simulated. To illustrate my approach, I will present our experiments with a vacuum-cleaning robot that tries to predict a user's intentions and its capabilities to infer if help is needed. I will conclude my talk with listing problems related to over-humanizing AI in order to spark a discussion about boundaries and limitations of too-human-like machines.