Technically Biased
Claim This Podcastby Krystyn Gutu
Podcast Overview
<p>The podcast that discusses bias in tech.</p><p><a href="https://gakovii.com/">Gakovii</a></p>
Language
🇺🇲
Publishing Since
5/10/2023
Reach the team behind Technically Biased
Verified contact details for this show aren't on file yet — sign up to get notified when they land.
Recent Episodes
May 8, 2024
Being Picky with Piki: Ironing out the Biases in Song Quality Algorithms
<p>Listen to <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/ACoAAB7ri9IBqVFo0_aHpFm_BQ2RPoRcRzhEGT4">Krystyn Gutu, M.S.</a> introduce <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/sasha-stoikov-b841075/">Sasha Stoikov</a>, a senior research associate at Cornell Financial Engineering in Manhattan (CFEM). His research studies algorithms in high-frequency financial trading, online ratings systems, and recommendation systems. In these various domains, he has come across algorithmic biases such as survivorship bias, popularity bias, and inflation bias.</p><p>He is also the founder of <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.piki.nyc/">Piki</a>, a startup that gamifies music ratings. Ratings produced by users on Piki can mitigate algorithmic biases, which he discusses in a recent paper, aimed at answering a simple but provocative question: “Are the popularities of artists like Justin Bieber or Taylor Swift truly justified?”</p><p>Check out his paper, <a target="_blank" rel="noopener noreferrer nofollow" href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4562658">Better Than Bieber? Measuring Song Quality Using Human Feedback</a>, to find out. He also authored <a target="_blank" rel="noopener noreferrer nofollow" href="https://arxiv.org/abs/2109.07692">Evaluating Music Recommendations with Binary Feedback for Multiple Stakeholders</a>, and <a target="_blank" rel="noopener noreferrer nofollow" href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4686185">Picky Eaters Make For Better Raters</a>. </p><p>In this episode, we discuss </p><p>– the roles of survivorship bias, popularity bias, and inflation bias </p><p>– Piki, the music ratings app designed exclusively for those who know what they like </p><p>– how algorithms like Instagram, TikTok, and Spotify compare to how Piki analyzes song quality </p><p>– data used to train these and other platforms </p><p>– how interfaces collecting data unintentionally encourage certain biases </p><p>– implicit vs explicit data collection </p><p>– how data is collected and how it addresses the main concerns of their users </p><p>– how Piki incentives its users to listen to a larger music selection and nudges them into being fair with their ratings </p><p>– the golden era of data and the tremendous opportunities and dangers that lie ahead</p><p></p><p>If you like what you hear, follow us on LinkedIn (@Gakovii) or on Instagram (@gakovii__).</p><p>Technically Biased is available on Spotify, Apple, and Amazon, among others.</p><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=algorithmicbias&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#AlgorithmicBias</a> <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=predatorytech&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#PredatoryTech</a> <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=technicallybiasedpodcast&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#TechnicallyBiasedPodcast #Gakovii</a></p><p></p>
April 24, 2024
Algorithmic Auditing... it's Not Rocket Science, it's Astrophysics
<p>Tune in to learn about the applicability of algorithmic auditing.</p><p>Guest, <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/shea-brown-26050465/">Shea Brown</a>, founder and CEO of <a target="_blank" rel="noopener noreferrer nofollow" href="https://babl.ai/">BABL AI</a>, joins us to share his perspective. An Associate Professor of Instruction at the University of Iowa, Brown has his PhD in Astrophysics and specializes in AI Ethics and Machine Learning, with a focus on Algorithmic Auditing and AI Governance.</p><p>In this episode, we discuss:</p><p>– Brown’s use of AI in astrophysics and its applicability, given the extent of data from the sky </p><p>– Brown’s transition to founding BABL AI after realizing a big problem: countless examples of bias in AI </p><p>– BABL AI and the consulting work they do and what the process entails </p><p>– algorithmic auditing which, like any audit, is a check and balance aimed at ensuring people and organizations meet the required standards and follow appropriate procedures (i.e., we don’t want to harm people, we don’t want to infringe on people’s rights, people should be involved in algorithmic decision-making, etc.) </p><p>– algorithmic auditing, with a focus on the socio-technical aspect of how tech is being used more broadly </p><p>– what to expect for the future of AI regulation and governance </p><p>– the importance of accountability and transparency, and the trade-offs that come with regulation </p><p>– algorithmic transparency, and whether your audience knows an algorithm is being used and the data being processed; accountability and transparency are important for building trust within a society which should demand more from the companies using their data </p><p>– how historical data will always hold a level of bias that needs to be considered</p><p></p><p>If you like what you hear, follow us on LinkedIn (@Gakovii) or Instagram (@gakovii__).</p><p>Technically Biased is available on Spotify, Apple, and Amazon, among others.</p><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=algorithmicbias&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#AlgorithmicBias</a> <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=predatorytech&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#PredatoryTech</a> <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=technicallybiasedpodcast&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#TechnicallyBiasedPodcast #Gakovii</a></p>
April 10, 2024
Muslim American Indentities and Their Many Facets
<p>Listen to <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/ACoAAB7ri9IBqVFo0_aHpFm_BQ2RPoRcRzhEGT4">Krystyn Gutu, M.S.</a> introduce <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/lindsay-lee-wallace-ba0822123/">Hauwa Abbas</a> and <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/lama-aboubakr-21597b76/">Lama Aboubakr</a>.</p><p>Abbas is the founder of <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.halimahproject.com/">The Halimah Project</a>, a mentoring and tutoring program created for refugee youth in the Greater Lansing (Michigan) Area. She is a graduate student at American University and a grant writer at Miftaah Institute.</p><p>Aboubakr runs her own <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.lamaaboubakr.com/">practice</a>, where she is a Mindset & Life Coach, combining cognitive psychology-based techniques with Islamic Spirituality coaching. She specializes in dating and relationships for Muslims.</p><p></p><p>Tune in to listen to them share their perspective on:</p><p>~ the work they do</p><p>~ working with Muslim refugee youth</p><p>~ working with Muslim and Muslim American couples / individuals and helping them navigate dating and relationships</p><p>~ the importance of faith and respect for Allah</p><p>~ the perpetuation of bias and microaggressions, internally and externally</p><p></p><p>If you like what you hear, follow us on any of our social media linked below.</p><p>Technically Biased is available on Spotify, Apple, and Amazon, among others.</p><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=algorithmicbias&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#AlgorithmicBias</a> <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=predatorytech&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#PredatoryTech</a> <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/feed/hashtag/?keywords=technicallybiasedpodcast&highlightedUpdateUrns=urn%3Ali%3Aactivity%3A7064634150900649984">#TechnicallyBiasedPodcast #Gakovii</a></p>
18 total episodes available
Deep-dive analytics for Technically Biased
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is Technically Biased?
<p>The podcast that discusses bias in tech.</p><p><a href="https://gakovii.com/">Gakovii</a></p> - How often does this podcast release new episodes?
This podcast updates weekly.
- Where can I listen to this podcast?
This podcast is available on 9 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
No, this podcast does not typically feature guests.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.