I was interviewed for the ABU‘s quarterly magazine Reflex, alongside Jarno Duursma, to respond to the statement: “AI is unbiased and leads to more inclusive labor market” (spoiler: I partly agree).
Read it online here

That was fun! The Online Anti-Discrimination Hackathon ran last weekend, a hakacthon co-organized by Ministerie van OCW, Inspectie SZW, Ministerie van BZK, and Hackathon Factory which revolved around “gender discrimination in data collection and labeling for automated assessment and selection of candidates.” Having ample experience in designing and developing AI-powered candidate selection systems, and the risks of algorithmic bias, I was happy to contribute to this hackathon with a few colleagues at Randstad Groep Nederland in several ways.
First, I gave a (virtual, pre-recorded) talk on algorithmic matching, algorithmic bias, and bias mitigation in the domain of automated recruitment. More specifically, I shared how and where we use AI and recommender systems to facilitate job and candidate matching at Randstad Groep Nederland, and more generally about the challenges of bias and the opportunities of bias mitigation. I showcased both examples of misuse of AI, which results in discriminatory systems, and examples of how AI can be used to actively reduce or mitigate bias in the recruitment process. See the recording of my talk below:
In addition, me and a colleague joined live interactive roundtable sessions during the hackathon, and we brought a panel of four subject-matter experts for one-on-one sessions with hackathon teams and participants.
Read moreIn the context of the upcoming workshop “AI and Journalism” Bennie Mols interviewed me for the website of the European Science-Media Hub, on how we apply AI in journalism for Het FD and BNR. Read the piece here:
Or read the more in-depth background interview here:
In response to my op-ed in Het Parool, Jim Stolze interviewed me and published the interview on the website of De Nationale AI Cursus (a free online course/MOOC on AI aimed at the general public); Read the article below:
I wrote a response on recent coverage around the alleged ‘promotion’ of anti-vax books by bol.com, suggesting it is due to “influential, steering, algorithms.” In this piece I state it’s not an issue of algorithms, but of long-tail, obscure, content. My response was published in Het Parool, as an edited letter. Read the original, unedited piece (in Dutch) below.
plopDe Volksrant wrote published an article on Dutch robo-journalism, where I’m featured on explaining our SMART Journalism recommender system + abstractive summarization plans.
Read the article by clicking on the image below:
And read more about our SMART Journalism project in our position paper:
@inproceedings{sappelli2018smart,
title={SMART Journalism: Personalizing, Summarizing, and Recommending Financial Economic News},
author={Sappelli, Maya and Chu, Dung Manh and Cambel, Bahadir and Graus, David and Bressers, Philippe},
booktitle={The Algorithmic Personalization and News (APEN18) Workshop at ICWSM '18},
year={2018}
}
In the latest AI Podcast, I am featured, talking with Li’ao Wang on our SMART Radio and SMART Journalism projects. Stream the episode below!
“Media is smart, but needs to get smarter. That’s what we’re working on here at the FD Mediagroep. Come and see what we do with AI to make our creators and content better.”
In the magazine IPΒ (“journal for information professionals”) I amΒ interviewed as one of three young professionals who show that ‘traditional categories and conceptual frames need to be readjusted.’
More specifically, it describes how my multi-disciplinary background, with an academic background in media studies, professional experience in the media, with a PhD in computer science, is important in bridging the gap between ‘techies’ and ‘non-techies’, and of particular value in my current role where I work on enabling AI in media.Β
In the context of a high-profile legal case (involving a bunch of data acquired from encrypted “Ennetcom” phones) I assisted lawyer Inez Weski in acquiring insights and trying to understand how digital forensic tools were used in the collection of digital evidence. I did this work in the context of my PhD research on semantic search for E-Discovery. In this post, I list some of the publications that followed from my work and the case.
Hansken is the search engine developed by the Netherlands Forensic Institute, and used by the police and public prosecutors. In this article in De Volkskrant, titled “Met deze eigen zoekmachine spit de politie schatten aan digitaal bewijs door,” I answered a few questions and explained my view on the role of Hansken in the court of law and digital evidence acquisition.
For more information on the case and my work, there’s a more in-depth piece on my work for Weski in the following NEMO Kennislink article, which details my findings and concerns with respect to using a proprietary, continuously developed, and largely black-box tool for collecting digital forensic evidence:
Finally, if you still didn’t have enough, there’s a blog post on crimesite which explains a bit more on the (legal) case, and some interpretations on my report and findings;
In RTL XL’s “How it’s done” me and Company.info’s CTO Henk Pijper explain why and how we apply AI and data science at Company.info to gain insights from online news.Β