On June 21st 2018, the KAIST Institute for Artificial Intelligence, Fourth Industrial Revolution Center in Korea hosted a public forum discussion on “Taming Artificial Intelligence: Engineering, Ethics, and Policy to discuss the ethics of artificial intelligence technology development as well as policy making around the world.
Continue reading KAIST workshop on Taiming AI: Engineering, Ethics and Policy
On March 5th and 6th UnBias had the pleasure of participating in a workshop that was organized to signal the launch of the European Commission’s Joint Research Center’s HUMAINT (HUman behaviour and MAchine INTelligence ) project.
The HUMAINT project is a multidisciplinary research project that aims to understand the potential impact of machine intelligence on human behaviour. A particular focus of the project lies on human cognitive capabilities and decision making. The project recognizes that machine intelligence may provide cognitive help to people, but that algorithms can also affect personal decision making and raise privacy issues.
Continue reading European Commission initiatives to explore regulatory requirements for AI
On September 14th the US ACM organized a panel on Algorithmic Transparency and Accountability in Washington DC to discuss the importance of the Statement on Algorithmic Transparency and Accountability and opportunities for cooperation between academia, government and industry around these principles. Also part of this panel was Ansgar, representing the IEEE Global Initiative on Ethical Considerations for Artificial Intelligence and Autonomous Systems, its P7000 series of Standards activities, and UnBias.
Just two days earlier, on September 12th, the IEEE news source The Institute published a blog article “Keeping Bias From Creeping Into Code“, based on an interview with Ansgar about the P7003 Standard for Algorithmic Bias Considerations.
Continue reading USACM Panel on Algorithmic Transparency and Accountability
USACM, the ACM U.S. Public Policy Council, will be hosting a panel event on “Algorithmic Transparency and Accountability.” The event will provide a forum for a discussion between stakeholders and leading computer scientists about the growing impact of algorithmic decision-making on our society and the technical underpinnings of algorithmic models.
Panelists will discuss the importance of the Statement on Algorithmic Transparency and Accountability and the opportunities for cooperation between academia, government and industry around these principles.
As part of our work to contribute to the development of the IEEE P7003 Standard for Algorithm Bias Considerations we are reaching out to the community of stakeholders to ask for use cases highlighting real-world instances of unjustified and/or inappropriate bias in algorithmic decisions.
Conference call to catch up on recent updates to the outline document for the P7003 IEEE Standard on Algorithm Bias Considerations.
The main item on the agenda for this call was identifying working group members who would want to volunteer to take the lead on developing specific sections of the outline document.
The list of past meeting minutes and agendas is available here.
Conference call to catch up on recent updates to the outline document for the P7003 IEEE Standard on Algorithm Bias Considerations.
The main item on the agenda for this call was identifying working group members who would want to volunteer to take the lead on developing specific sections of the outline document.
The list of past meeting minutes and agendas is available here.
IEEE Standards Association (IEEE-SA) invites your participation in the IEEE P7003™, Standard for Algorithmic Bias Considerations Working Group.
Why get involved:
The goal of this Standard Project is to describe specific methodologies that can help users certify how they worked in order to address and eliminate issues of negative bias in the creation of their algorithms. “Negative bias” refers to the usage of overly subjective or uniformed data sets or information known to be inconsistent with legislation concerning certain protected characteristics (such as race, gender, sexuality, etc.); or with instances of bias against groups not necessarily protected explicitly by legislation, but otherwise diminishing stakeholder or user wellbeing and for which there are good reasons to be considered inappropriate.
Who should participate:
Programmers, manufacturers, researchers or other stakeholders involved in creating an algorithm along with any stakeholders defined as end users of the algorithm, and any non-user affected by the use of the algorithm, including but not limited to customers, citizens or website visitors
How to Participate:
If you wish to participate in the IEEE P7003™ Working Group, please contact the Working Group Chair, Ansgar Koene.
Meeting Information:
The first IEEE P7003™ Working Group meeting will be held online via (WebEx) on Friday, 5 May from 9:00 AM – 11:00 AM (EST)
If you cannot attend the meeting and want to be added to the distribution list please fill out this form.
As part of our stakeholder engagement work towards the development of algorithm design and regulation recommendations UnBias is engaging with the IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems to develop an IEEE Standard for Algorithm Bias Considerations, designated P7003. The P7003 working group is chaired by Ansgar Koene and will have its first web-meeting on May 5th 2017.
Continue reading IEEE Standard for Algorithm Bias Considerations
The IEEE Standards Association (IEEE-SA) Corporate Membership Program invites you to join an exclusive webinar.
18 April 2017 at 12:00PM- 1:00PM EDT
In the age of autonomous and intelligent machines, it is more important than ever to help technologists and organizations be cognizant of the ethical implications of the products, services or systems they are building and how they are being built before making them available to the general public. While established Codes of Ethics provide instrumental guidance for employee behavior, new values-centric methodologies are needed to complement these codes to address the growing use of algorithms and personalization in the marketplace.
Key insights from the Working Group Chairs of three IEEE-SA projects will be presented. The IEEE Global Initiative provided the input and recommendations that led to the creation of Working Groups for these IEEE-SA standards projects:
IEEE P7001™: Transparency of Autonomous Systems
IEEE P7003™: Algorithmic Bias Considerations
Speakers will provide their perspectives on why it is important for business leaders to increase due diligence relative to ethical considerations for what they create. This focus is not just about avoiding unintended consequences, but also increasing innovation by better aligning with customer and end-user values.
Kay Firth-Butterfield
Executive Committee Vice-Chair, The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems, Executive Director, AI Austin
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John C. Havens
Executive Director, The IEEE Global Initiative for Ethical Considerations In Artificial Intelligence and Autonomous Systems
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Konstantinos Karachalios
Managing Director, IEEE Standards Association SEE FULL BIO
Ansgar Koene
Senior Research Fellow at Horizon Digital Economy Research institute, University of Nottingham. Co-Investigator on the UnBias project and Policy Impact lead for Horizon.
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Alan Winfield
Professor, Bristol Robotics Laboratory, University of the West of England; Visiting Professor, University of York
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