Congratulations to Will Hawkins, MSc Social Science of the Internet (part-time)
Thesis title: Seeking Disclosure: Rethinking research ethics in the age of AI data enrichment
Supervisor: Director of Research, Associate Professor, Senior Research Fellow Dr Brent Mittelstadt, Oxford Internet Institute
Will said: “I am so grateful to receive this award! Being able to spend time exploring the ethical implications of AI research and the data enrichment required to develop machine learning models at the OII has been a fantastic experience. I am so thankful for all of the time and support of my supervisor, Prof Brent Mittelstadt, who could not have been more thoughtful and patient throughout the process, and from whom I’ve learnt so much. I’ve also loved being a part of the OII community, particularly my part-time cohort who have been a huge part of the last two years. Finally, I’d also like to thank Chrissy Bunyan & David Pepper, who have been central to my experience in Oxford and without whom I cannot imagine the OII”.
In congratulating Will, Dr Brent Mittelstadt said,
“I am tremendously delighted for Will to receive this award, and can think of no one more deserving. Much ink has been spilled on the problems of bias and accountability in how AI is designed and deployed, but comparatively little attention has been given to the responsibilities of data scientists and developers in how they collect and curate the data that drives these systems. Data enrichment is an incredibly important aspect of AI development, and yet it falls through the cracks of research ethics and other oversight mechanisms. Will’s insightful and timely thesis shines a light on this essential issue for AI governance, revealing the failures of AI development as currently practiced while paving a clear path forward that shows how the field as a whole can, and must, do better. I’m convinced Will’s pioneering research will serve as a foundational work in AI ethics in the years to come”.
Congratulations to Sarah Ball, MSc Social Data Science
Thesis title: Triple standard in venture financing? The impact of an entrepreneur’s gender on investment decisions in equity crowdfunding
Supervisor: Senior Research Fellow, Dr Bernie Hogan, Oxford Internet Institute
Sarah said; “I am deeply honoured to receive the OII thesis prize. When I began the MSc in Social Data Science, I never imagined that I would one day be writing these words. From the very first week of Michaelmas, I have been continuously impressed by the brilliance of both my peers and the teaching staff. Coming from a wide range of disciplines, they have inspired my thinking day after day, and I have learned so much from each one of them. My special thanks go to my supervisors, Prof Luciano Floridi and Dr Bernie Hogan, for their constant belief in my abilities and their tireless support throughout this journey. I would also like to express my gratitude to the OII for providing financial support for this thesis project. My hope is that this thesis will stimulate further research into how alternative financing sources, such as crowdfunding, can lead to fairer investment decisions by democratising the funding process.”
In congratulating Sarah, Dr Hogan said, “It is incredibly exciting to see Sarah Ball receive this award for her thesis. Her work is both incredibly sound work coming from psychology and organisational behaviour but also meaningfully speaking to online crowdsourcing and identity. Her work identifies clear mechanisms whereby perceptions of competence mediate one’s willingness to fund a crowdsourced project. This competence is further moderated by perceptions by gender. In this matter Sarah’s work has been innovative and sound. She used synthetic images by gender including nonbinary persons in a creative experimental design. She used a sophisticated power analysis to be confident in sample size and claims. She was able to put skills in simulations, Python, JavaScript, web design and AI together in a forward thinking package for an online experiment. Her work helps us not only understand how gender plays a role in crowdsourced funding, but how people perceive gender in the first place.”
Congratulations to Conrad Borchers, MSc Social Data Science
Thesis title: Stack Overflow Correlation Networks Predict Technology Evolution and Labor Market Relevance
Supervisor: Dr Fabian Braesemann, Departmental Lecturer, Oxford Internet Institute
Conrad said, “I am humbled to receive the OII 2022 MSc Thesis Prize. Completing my thesis research at the intersection of economics and social data science has been an enriching experience and reinforced my love of research. It was a pleasure to grapple with a large body of theory on technological innovation and square it with nascent data streams on Stack Overflow technology relatedness. The increasing accessibility of large-scale data allows us to see established bodies of theory in a new light. In my thesis, investigating the logic of innovation through large-scale data opened new doors for real-world application of predicting job market developments ahead of time. This combination of rigorous theoretical work and the desire to shape real-world impact is what the OII instilled in me and makes it a unique place to learn. I want to thank my thesis advisor Dr. Fabian Braesemann, my MSc cohort, and the OII for their support and a gratifying year that I will always remember dearly”.
In congratulating Conrad, Dr Braesemann said:
“I’m proud of Conrad for his work. Conrad and I are currently in the process of turning the thesis into a manuscript for publication with the journal Royal Society Interface, as we believe the findings deserve to be shared with the academic community of technology scholars. The thesis makes an important contribution towards the quantification of technological progress with big online data”.
Highly Commended: Tom Williams
Thesis title: AI Ethics in the Real World: Bridging the gap between principles and practice in the development of artificial intelligence
Highly Commended: Matt Chapman
Thesis title: A recipe for gentrification: Predicting urban change with Tripadvisor data and machine learning,