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<h1><a href="" style="text-decoration: none; color: #222">Roseline Polle</a></h1>
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Roseline Polle<br>
Senior AI auditor<br>
AI Governance<br>
<!-- polle.roseline@gmail.com<br> -->
London, UK
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<h2><a href="">Bio <svg class="svg-inline--fa fa-link fa-w-16 anchor-link" aria-hidden="true" data-prefix="fas" data-icon="link" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" data-fa-i2svg=""><path fill="currentColor" d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg><!-- <i class="fas fa-link anchor-link"></i> --></a></h2>
<p>
I am a senior AI auditor, looking for opportunities to conduct research in Mechanistic Interpretability. I worked as a Responsible AI auditor and researcher at <a href="https://www.holisticai.com/">Holistic AI</a> for 3 years, performing a high number of early AI audits in various sectors, such as recruitment, facial recognition and financial services. I was also part of the UCL research team carrying out four pilots to improve empirical evidence around AI assurance during the <a href="https://cdei.blog.gov.uk/2021/04/15/the-need-for-effective-ai-assurance/">2020 CDEI programme of work on that subject</a>.
I participated in the development of material for two AI ethics courses for the Alan Turing Institute: Assessing and mitigating bias and discrimination in AI <a href="https://www.turing.ac.uk/courses/assessing-and-mitigating-bias-and-discrimination-ai">1</a> & <a href="https://www.turing.ac.uk/courses/assessing-and-mitigating-bias-and-discrimination-ai-beyond-binary-classification">2</a>, as well as give live workshops and talks around these subjects, notably at the <a href="https://www.youtube.com/watch?v=Abo3RK6EO3o&ab_channel=DevoxxUK">2023 Devoxx conference in London</a>.
Before this, I used to develop computational models for the Clean Energy sector at Bloomberg New Energy Finance.
<br><br>
I have a strong mathematical and scientific background from my degree at Ecole Polytechnique (France) and Msc in Machine Learning at UCL.
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<h2><a href="">Publications <svg class="svg-inline--fa fa-link fa-w-16 anchor-link" aria-hidden="true" data-prefix="fas" data-icon="link" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" data-fa-i2svg=""><path fill="currentColor" d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg><!-- <i class="fas fa-link anchor-link"></i> --></a></h2>
<div class="pub-item">
<span class="authors">Nigel Kingsman, Emre Kazim, Ali Chaudhry, Airlie Hilliard, Adriano Koshiyama, Roseline Polle, Giles Pavey & Umar Mohammed</span>
<span class="year">(2022).</span>
<span class="title"><a href="https://doi.org/10.1007/s44163-022-00018-4">Public sector AI transparency standard: UK Government seeks to lead by example.</a>.</span>
<span class="journal"><i>Discov Artif Intell</i>.</span>
<span class="doi-text"><a href="https://doi.org/10.1007/s44163-022-00018-4">https://doi.org/10.1007/s44163-022-00018-4</a></span>
</div>
<div class="pub-item">
<span class="authors">Hilliard, Airlie and Kazim, Emre and Koshiyama, Adriano and Zannone, Sara and Trengove, Markus and Kingsman, Nigel and Polle, Roseline</span>
<span class="year">(2022).</span>
<span class="title"><a href="http://dx.doi.org/10.2139/ssrn.4083189">Regulating the Robots: NYC Mandates Bias Audits for Ai-Driven Employment Decisions.</a>.</span>
<span class="journal"><i>SSRN</i>.</span>
<span class="doi-text"><a href="http://dx.doi.org/10.2139/ssrn.4083189">http://dx.doi.org/10.2139/ssrn.4083189</a></span>
</div>
<div class="pub-item">
<span class="authors">Polle, Roseline; Kazim, Emre; Carvalho, Graca; Koshiyama, Adriano; Inness, Catherine; Knight, Andrew; Gorski, Caroline; Barber, David; Lomas, Elizabeth; Yilmaz, Emine; Thompson, Gary; Ahamat, Ghazi; Pavey, Giles; Platts, Katie; Szpruch, Lukasz; Gregorovic, Miro; Rodrigues, Miguel; Ugwudike, Pamela; Nachev, Parashkev; Rai, Peter; Treleaven, Philip; Goebel, Randy</span>
<span class="year">(2021).</span>
<span class="title"><a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3935987">Towards AI Standards: Thought-Leadership in Ai Legal, Ethical and Safety Specifications Through Experimentation</a>.</span>
<span class="journal"><i>SSRN</i>.</span>
<span class="doi-text"><a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3935987">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3935987 </a></span>
</div>
<div class="pub-item">
<span class="authors">Emre Kazim, Adriano Soares Koshiyama, Airlie Hilliard and Roseline Polle</span>
<span class="year">(2021).</span>
<span class="title"><a href="https://doi.org/10.3390/jintelligence9030046">Systematizing Audit in Algorithmic Recruitment.</a>.</span>
<span class="journal"><i>Journal of Intelligence</i>.</span>
<span class="doi-text"><a href="https://doi.org/10.3390/jintelligence9030046">https://doi.org/10.3390/jintelligence9030046 </a></span>
</div>
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<h2><a href="">Other resources<svg class="svg-inline--fa fa-link fa-w-16 anchor-link" aria-hidden="true" data-prefix="fas" data-icon="link" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" data-fa-i2svg=""><path fill="currentColor" d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg><!-- <i class="fas fa-link anchor-link"></i> --></a></h2>
<ul>
<li>Blog post for the Institute of the Future of Work (IFOW): <a href="https://www.ifow.org/news-articles/fair-enough-intersectionality-in-machine-learning"> Fair enough? Intersectionality in machine learning</a>.</li>
<li>Talk for Devoxx 2023: <a href="https://www.devoxx.co.uk/talk/?id=10138"> Bias in Machine Learning at Devoxx 2023</a>.</li>
<li>Open access course for the Alan Turing Institute: <a href="https://www.turing.ac.uk/courses/assessing-and-mitigating-bias-and-discrimination-ai"> Assessing and Mitigating Bias and Discrimination in AI</a>.[<a href="https://github.com/alan-turing-institute/bias-in-AI-course">Github</a>]</li>
<li>Open access course for the Alan Turing Institute: <a href="https://www.turing.ac.uk/courses/assessing-and-mitigating-bias-and-discrimination-ai-beyond-binary-classification"> Assessing and mitigating bias and discrimination in AI: Beyond binary classification</a>.[<a href="https://github.com/alan-turing-institute/Bias-in-AI-beyond-binary-course">Github</a>]</li>
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<a class="anchor" id="creative-projects"></a>
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<h2><a href="">Creative project <svg class="svg-inline--fa fa-link fa-w-16 anchor-link" aria-hidden="true" data-prefix="fas" data-icon="link" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" data-fa-i2svg=""><path fill="currentColor" d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg><!-- <i class="fas fa-link anchor-link"></i> --></a></h2>
<ul>
<p><a href="https://football-opera.up.railway.app/">Football Opera: Sonification of football data</a>.
Dash app turning data from a football match into music. Published alongside a written piece in the <a href="https://thesideline.org/buy-issue-one">The Sideline magazine</a>.</p>
</ul>
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<a class="anchor" id="cv"></a>
<div class="docs-section examples">
<h2><a href="">CV <svg class="svg-inline--fa fa-link fa-w-16 anchor-link" aria-hidden="true" data-prefix="fas" data-icon="link" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" data-fa-i2svg=""><path fill="currentColor" d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg><!-- <i class="fas fa-link anchor-link"></i> --></a></h2>
<p>[<a href="https://www.roselinepolle.com/vita.pdf">pdf</a>]</p>
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