On 16th April the House of Select Committee on Artificial Intelligence published a report called ‘AI in the UK: ready, willing and able?”. The report is based on an inquiry by the House of Lords conducted to consider the economic, ethical and social implications of advances in artificial intelligence. UnBias team member Ansgar Koene submitted written evidence based on the combined work of the UnBias investigations and our involvement with the development of the IEEE P7003 Standard for Algorithmic Bias Considerations.
In the spirit of recent events surrounding the revelations about Cambridge Analytica and the breaches of trust regarding Facebook and personal data, ISOC UK and the Horizon Digital Economy Research institute held a panel discussion on “Multi Sided Trust for Multi Sided Platforms“. The panel brought together representatives from different sectors to discuss the topic of trust on the Internet, focusing on consumer to business trust; how users trust online services that are offered to them. Such services include, but are not limited to, online shopping, social media, online banking and search engines.
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.
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.
Prior to the June 8th snap election there were two Commons Select Committee inquiries that both touched directly on our work at UnBias and for which we submitted written evidence. One on “Algorithms in decision-making” and another on “Fake News”.
It is our great pleasure to welcome you to the 2nd UnBias stakeholder workshop this June 19th (2017) at the Wellcome Collection in London, UK.
In this workshop we will build on the outcomes of the previous workshop, moving from the exploration of issues to a focus on solutions.
Aims of stakeholder workshops Our UnBias stakeholder workshops bring together individuals from a range of professional backgrounds who are likely to have differing perspectives on issues of fairness in relation to algorithmic practices and algorithmic design. The workshops are opportunities to share perspectives and seek answers to key project questions such as:
What constitutes a fair algorithm?
What kinds of (legal and ethical) responsibilities do internet companies have to ensure their algorithms produce results that are fair and without bias?
What factors might serve to enhance users’ awareness of, and trust in, the role of algorithms in their online experience?
How might concepts of fairness be built into algorithmic design?
The workshop discussions will be summarised in written reports and will be used to inform other activities in the project. This includes the production of policy recommendations and the development of a fairness toolkit consisting of three co-designed tools 1) a consciousness raising tool for young internet users to help them understand online environments; 2) an empowerment tool to help users navigate through online environments; 3) an empathy tool for online providers and other stakeholders to help them understand the concerns and rights of (young) internet users.
Structure of the 2nd stakeholders workshop The workshop will consist of two parts.
In the first part we will present a challenge to choose which out of four possible algorithms is most fair for a limited resources allocation task. We will do this under two transparency conditions: 1. when only observations of outcomes are known; 2. when the rational behind the algorithm is know. we will conclude this part with a discussion about the reasoning behind our algorithm choices.
Having been primed with some of the challenges for designing fair algorithmic decision systems, the second part will explore ideas and frameworks for an ’empathy’ tool to help algorithmic system designers identify possible sources of bias in their system design.
12:00-1:00pm Lunch/informal networking
1:00 – 1:15 Brief introduction with update about the UnBias project & outline of the workshop
Privacy/confidentiality and data protection
All the workshops will be audio recorded and transcribed. This in order to facilitate our analysis and ensure that we capture all the detail of what is discussed. We will remove or pseudonymise the names of participating individuals and organisations as well as other potentially identifying details. We will not reveal the identities of any participants (except at the workshops themselves) unless we are given explicit permission to do so. We will also ask all participants to observe the Chatham House rule – meaning that views expressed can be reported back elsewhere but that individual names and affiliations cannot.
A number of pre and side events will be enriching the EuroDIG programme. European organisations will organise meetings on day zero 5th June and the European Commission opens the High Level Group on Internet Governance Meeting on 8th June to the public.
Our slogan is“Always open, always inclusive and never too late to get involved!”
Org Teams did their best to facilitate the ground for in depth multistakeholder discussion and our Estonian host, the Ministry of Foreign Affairs, worked hard to give you a warm welcome!
Now it is up to you to engage in the discussion – the floor is always open! A first opportunity will be the open mic session, the first session after the welcome.
We would like to hear from YOU:How I am affected by Internet governance?
No chance to travel to Tallinn?
No problem! We are in Estonia, the most advanced country in Europe when it comes to digital futures! For all workshops and plenary sessions we provide, video streaming (passive watching), WebEx (active remote participation) and transcription. Transcripts and videos will be provided at the EuroDIG wiki after the event. Please connect via the links provided in the programme.
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.
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)
The workshop took place on February 3rd 2017 at the Digital Catapult centre in London, UK. It brought together participants from academia, education, NGOs and enterprises to discuss fairness in relation to algorithmic practice and design. At the heart of the discussion were four case studies highlighting fake news, personalisation, gaming the system, and transparency.