To what extent can AI/statistical systems support the criminal justice process? Can we rely on algorithmic calculations to help us make decisions about whether an offender should receive a prison sentence? Are sentencing decisions made by statistical systems more or less likely to be flawed than those made by humans? As the use of AI in criminal justice systems around the world continues to grow, these questions become more and urgent to discuss – and were the focus of a recent roundtable discussion held at Oxford.
Continue reading Roundtable on Uses of Artificial Intelligence in the Criminal Justice System
HOW DO YOU TAKE CARE ON THE INTERNET?
Members of the UnBias team and the Digital Wildfire project from the Universities of Nottingham and Oxford were delighted to participate in Mozilla Festival (MozFest), which took place over the weekend of 28th-29th October 2017. The festival saw thousands of members of the general public, of all ages and nationalities, pass through the doors of Ravensbourne College to engage in a festival that aimed to promote a healthy internet and a web for all. Issues of digital inclusion, web literacy and privacy and security were some of the key topics that were discussed at the event.
Continue reading HELLO FROM MOZFEST!
How do you take care on the Internet? What are the dangers of online fake news and filter bubbles? What are appropriate punishments for hate speech and trolling?
These are questions we asked members of the public during the Curiosity Carnival at the University of Oxford on September 30th. The Curiosity Carnival formed part of European Researchers’ Night, celebrated in cities across Europe. Oxford ran a city wide programme of activities across its universities, libraries, gardens and woods to give members of the public a chance to find out about real research projects and meet the people who conduct them.
Continue reading UnBias takes part in European Researchers’ Night!
In the current BBC series Secrets of Silicon Valley Jamie Bartlett (technology writer and Director of the Centre for Social Media Analysis at Demos) explores the ‘dark reality behind Silicon Valley’s glittering promise to build a better world.’ Episode 2, The Persuasion Machine, shines a spotlight on several of the issues we are investigating in UnBias.
Continue reading Algorithms and the persuasion machine
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.
Continue reading A call for use case examples
June was a month of conferences and workshops for UnBias. The 3rd UnBias project meeting on June 1st, hosted by our Edinburgh partners this time, was quickly followed by the Ethicomp and EuroDIG conferences which both took place from June 5th to 8th.
Continue reading A Month of Conferences and Workshops
The 4th Winchester Conference on Trust, Risk, Information and the Law took place at the University of Winchester on Wednesday 3rd May 2017. The overarching theme of the day was “Artificial and De-Personalised Decision-Making: Machine-Learning, A.I. and Drones”: offering a chance for multi-stakeholder and interdisciplinary discussion on the risks and opportunities presented by algorithms, machine learning and artificial intelligence.
Continue reading UnBias project contribution to the 4th Winchester Conference on Trust, Risk, Information and the Law
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
Many multi-user scenarios are characterised by a combinatorial nature, i.e., an algorithm can take meaningful decisions for the users only if all their requirements and preferences are considered at the same time to select a solution from a huge potential space of possible system decisions. Sharing economy application, where users aim to find peers to form teams with in order to accomplish a task, and situations in which a limited number of potentially different resources, e.g. hotel rooms, must be distributed to users who have preferences over them are examples of such scenarios.
Continue reading How hard is to be fair in multi-user combinatorial scenarios?
On 21st March the House of Select Committee on Communications published a report called ‘Growing up with the internet’. The report is based on an enquiry conducted by the House of Lords into Children and the Internet. UnBias team member Professor Marina Jirotka served as a specialist advisor to the enquiry and team member Professor Derek McAuley gave verbal evidence to it, elaborating on the written evidence submitted by Perez, Koene and McAuley.
Continue reading “Growing up Digital” UnBias team members contribute to House of Lords report