Data Ethics Club Social Special: Data Ethics Club: Creating a collaborative space to discuss data ethics#
What’s this?
This is summary of Wednesday 6th November’s Data Ethics Club discussion, where we spoke and wrote about Data Ethics Club! For reading, you could check out our paper Data Ethics Club: Creating a collaborative space to discuss data ethics by Nina H. Di Cara, Natalie Zelenka, Huw Day, Euan D.S. Bennet, Vanessa Hanschke, Valerio Maggio, Ola Michalec, Charles Radclyffe, Roman Shkunov, Emma Tonkin, Zoë Turner, and Kamilla Wells. The summary was written by Jessica Woodgate, who tried to synthesise everyone’s contributions to this document and the discussion. “We” = “someone at Data Ethics Club”. Huw Day, Amy Joint, Vanessa Hanschke, Nina Di Cara and Natalie Thurlby helped with the final edit.
Discussion Summary#
For this instalment of Data Ethics Club, we had a bit more relaxed, getting-to-know-each-other type session. The very optional reading is the DEC paper Data Ethics Club: Creating a collaborative space to discuss data ethics where we present the ideas behind and organisation of Data Ethics Club.
What’s something you all have in common?#
Despite our different backgrounds, we have similar approaches to how we use and think about data. A lot of us are problem solvers and communicators, and we are all passionate about data ethics. Some of us also share experience in teaching or research. The combination of problem solving skills and interest in ethics fosters the desire to question the world around us. After encountering a few questionable scenarios with data, we began to examine the ethical question. We use Data Ethics Club (DEC) as an avenue to discuss why it is that we use data in the ways that we do.
Participating in discussions at DEC has helped us to learn things about data ethics that we can take into other aspects of our lives. In our own work there are lots of questions that arise regarding data handling, privacy, anonymity, etc. which relate to data ethics. We have encountered colleagues who are interested in data ethics and using data correctly but find it hard to provide straightforward solutions or answers. Previous to coming along to DEC, we were curious but apprehensive to form opinions. We come to DEC because we are interested in hearing other peoples’ views about data, learning more about AI and ethics, and gaining more understanding on how we approach the ethical side of AI. Identifying with different experiences at DEC exposes us to a range of perspectives and new insights.
Encountering different perspectives at DEC is helpful when we have to convince or inform others regarding data ethics and safety - something that many of us have experienced. Sometimes we have had to warn people to not just send data insecurely via email. We’ve found it difficult to significantly engage with getting back to people regarding secondary data usage. We use our skills to help companies be more inclusive by thinking about data collection and ethics, trying to ensure that fairness is applied in building risk profiles or making predictions. To implement data ethics, Data Hazards is a useful project to help structure data ethics assessments and Diversily work towards empowering businesses to be more inclusive. Diversily have a playbook to help product designers and innovators contribute to a more equitable world.
Research is something that we strongly feel should be accessible by anyone, anywhere. However, when we’ve worked with second hand data we’ve found that processes to access data are complicated and ethical assessment is unevenly applied. Paradigms should be adjusted to put end users and data owners at the heart of data science. We are passionate about implementing participatory research; people need to be part of research to understand how their data will be used and the consequences of providing their data. On an institutional level, involving research participants and safeguarding secondary uses of their data is challenging when there is no ongoing contact with people from whom data is sourced. We would like participants to be involved in future decisions involving their data.
Good data management and secondary data usage is undeniably important, yet we have found there to be a lot of competing standards or uneven approaches when it comes to data handling. One relevant application for data management is medicine. Some of us have experience working in medical research or clinical trials and were shocked by the lack of respect for peoples’ data, such as there being no protection over peoples’ signatures or email collections. We also have experience working with genetic data, from which lots of data handling questions arise including who has access to the data and who safeguards the data.
Through our interests in data ethics and systemic issues we have been incentivised to diversify our skills base such as improving our maths. Some of us are polymaths and can cross between different fields with ease. Many of us have had changed career directions, which we have found to be highly rewarding. We encourage people to scratch the itch and try a variety of things.
What’s something that makes you all different?#
Many different paths have taken us to DEC, coming from an array of backgrounds including maths, zoology, philosophy, astrophysics, English, teaching, product management, and the civil service. Diverse backgrounds are a feature, not a bug of DEC. It’s not possible for someone to be an expert in absolutely everything, so interdisciplinary group effort is needed to tackle difficult problems.
Diversity fuels good discussions. Often people come to DEC thinking they have no relevant experience and intending to stay on mute, then later realising that they do have things to add. We would like anybody to feel welcome at DEC - “if websites came with a counter on how many times the organisers have broken the website, DEC would probably be a lot less intimidating”. Our varying use cases and applications mean that we come to data ethics with different angles. Different angles enrichen discussions to gently nudge people into forming opinions where they might not have had opinions before, or question previously held opinions.
As a group, if you hypothetically had unlimited time and unlimited money, what would you do to try and put your Data Ethics knowledge into use for societal good?#
We see data ethics as leading to data justice, from which we can take actionable insights to initiate change. Ethics is not just something that is done in a dusty old room; it can be done anywhere. We would like to widen involvement in ethics by pursuing outreach and research on how to help people manage or safeguard their data.
Ethical approval of better, clearer, and diverse data should be the base level from which AI development begins. Streamlining ethical approval processes would improve AI development from a data ethics standpoint. Working on how we talk about AI is also important. We and AI work towards enabling critical thinking around AI, and better images of AI is campaigning to counter harmful stereotypes surrounding AI. The video I, HATE, I, ROBOT led us to talk about creating a film called “I, data” with someone unknown in acting, an evolution from “I, robot”.
However, trying to do not for profit data science is difficult; time and money are crucial to pursue projects to fruition.
Attendees#
Huw Day, Data Scientist, Jean Golding Institute, University of Brhttps://www.linkedin.com/in/huw-day/
Amy Joint, Programme Manager, ISRCTN (UK’s Clinical Study Registry)
Zoë Turner, Senior Data Scientist, NHS Midlands and Lancashire CSU (Strategy Unit) and NHS-R Community
Euan Bennet, Lecturer, University of Glasgow
Ismael Kherroubi Garcia, AI Ethics Consultant, Kairoi
Kamilla Wells, Citizen Developer, Australian Public Service, Brisbane
Chris Jones, Data Scientist
Zosia Beckles, Research Information Analyst, University of Bristol
Bing Wang, EPR Senior Configuration Designer, Great Ormond Street Hospital for Children NHS Foundation Trust, London
Christina Palantza, PhD student at the University of Bristol