Artificial Intelligence/Operations Research Workshop 2 Report Out
- URL: http://arxiv.org/abs/2304.04677v1
- Date: Mon, 10 Apr 2023 15:51:39 GMT
- Title: Artificial Intelligence/Operations Research Workshop 2 Report Out
- Authors: John Dickerson, Bistra Dilkina, Yu Ding, Swati Gupta, Pascal Van
Hentenryck, Sven Koenig, Ramayya Krishnan, Radhika Kulkarni, Catherine Gill,
Haley Griffin, Maddy Hunter, Ann Schwartz
- Abstract summary: This Report Out focuses on the foundational elements of trustworthy AI and OR technology, and how to ensure all AI and OR systems implement these elements in their system designs.
Four sessions on various topics within Trustworthy AI were held, these being Fairness, Explainable AI/Causality, Robustness/Privacy, and Human Alignment and Human-Computer Interaction.
Following discussions of each of these topics, workshop participants also brainstormed challenge problems which require the collaboration of AI and OR researchers and will result in the integration of basic techniques from both fields to eventually benefit societal needs.
- Score: 38.11462021949535
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This workshop Report Out focuses on the foundational elements of trustworthy
AI and OR technology, and how to ensure all AI and OR systems implement these
elements in their system designs. Four sessions on various topics within
Trustworthy AI were held, these being Fairness, Explainable AI/Causality,
Robustness/Privacy, and Human Alignment and Human-Computer Interaction.
Following discussions of each of these topics, workshop participants also
brainstormed challenge problems which require the collaboration of AI and OR
researchers and will result in the integration of basic techniques from both
fields to eventually benefit societal needs.
Related papers
- From Stem to Stern: Contestability Along AI Value Chains [21.781422547251676]
This workshop will grow and consolidate a community of interdisciplinary CSCW researchers focusing on the topic of contestable AI.
As an outcome of the workshop, we will synthesize the most pressing opportunities and challenges for contestability along AI value chains in the form of a research roadmap.
Considering the length and depth of AI value chains, it will especially spur discussions around the contestability of AI systems along various sites of such chains.
arXiv Detail & Related papers (2024-08-02T06:57:52Z) - The Ethics of AI in Education [0.0]
The transition of Artificial Intelligence from a lab-based science to live human contexts brings into sharp focus many historic, socio-cultural biases, inequalities, and moral dilemmas.
Questions that have been raised regarding the broader ethics of AI are also relevant for AI in Education (AIED)
AIED raises further challenges related to the impact of its technologies on users, how such technologies might be used to reinforce or alter the way that we learn and teach, and what we, as a society and individuals, value as outcomes of education.
arXiv Detail & Related papers (2024-03-22T11:41:37Z) - Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness [53.91018508439669]
The study explores the complexities of integrating Artificial Intelligence into Autonomous Vehicles (AVs)
It examines the challenges introduced by AI components and the impact on testing procedures.
The paper identifies significant challenges and suggests future directions for research and development of AI in AV technology.
arXiv Detail & Related papers (2024-02-21T08:29:42Z) - Human AI Collaboration in Software Engineering: Lessons Learned from a
Hands On Workshop [1.14603174659129]
The study identifies key themes such as the evolving nature of human AI interaction, the capabilities of AI in software engineering tasks, and the challenges and limitations of integrating AI in this domain.
The findings show that while AI, particularly ChatGPT, improves the efficiency of code generation and optimization, human oversight remains crucial, especially in areas requiring complex problem solving and security considerations.
arXiv Detail & Related papers (2023-12-17T06:31:05Z) - Report of the 1st Workshop on Generative AI and Law [78.62063815165968]
This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw)
A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal, and policy challenges presented by law for Generative AI.
arXiv Detail & Related papers (2023-11-11T04:13:37Z) - The Road to a Successful HRI: AI, Trust and ethicS-TRAITS [64.77385130665128]
The aim of this workshop is to foster the exchange of insights on past and ongoing research towards effective and long-lasting collaborations between humans and robots.
We particularly focus on AI techniques required to implement autonomous and proactive interactions.
arXiv Detail & Related papers (2022-06-07T11:12:45Z) - On some Foundational Aspects of Human-Centered Artificial Intelligence [52.03866242565846]
There is no clear definition of what is meant by Human Centered Artificial Intelligence.
This paper introduces the term HCAI agent to refer to any physical or software computational agent equipped with AI components.
We see the notion of HCAI agent, together with its components and functions, as a way to bridge the technical and non-technical discussions on human-centered AI.
arXiv Detail & Related papers (2021-12-29T09:58:59Z) - Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and
Stir" [76.44130385507894]
This paper aims to ground what we dub a 'participatory turn' in AI design by synthesizing existing literature on participation and through empirical analysis of its current practices.
Based on our literature synthesis and empirical research, this paper presents a conceptual framework for analyzing participatory approaches to AI design.
arXiv Detail & Related papers (2021-11-01T17:57:04Z) - AI in society and culture: decision making and values [0.0]
Several academic debates, social consultations and impact studies are available to reveal the key aspects of the changing human-machine ecosystem.
In details, sociocultural filters, taxonomy of human-machine decisions and perspectives of value-based AI are in the focus of this literature review.
For better understanding, it is proposed to invite stakeholders in the prepared large-scale survey about the next generation AI that investigates issues that go beyond the technology.
arXiv Detail & Related papers (2020-04-29T07:09:39Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.