ΑΙhub.org
 

The Machine Ethics Podcast: Algorithms with social impact with Mitchel Ondili


by
06 January 2023



share this:

Mitchel Ondili
Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology’s impact on society.

The Politics of AI

This episode we talk with Mitchel Ondili on algorithm awareness, technology colonisation in the global south, the Observatory of Algorithms with Social Impact (OASI) and submitting your algorithms there, AI auditing, private vs public rights to consent, hiring and social services algorithms, the over-datafication of life, becoming an algorithmic subject, intentionality of services and much more.

Listen to the episode here:

Mitchel Ondili is a lawyer and tech policy professional, and recognized as a Women Deliver Young Leader, a New Emerging openAIR researcher and a member of the Feminist AI research network. Her primary areas of interest are the impact of internet communications on democratic practices, open data, artificial intelligence, and the public digital sphere.

At Eticas, Mitchel leads the Observatory of Algorithms with Social Impact (OASI) and provides support to different projects looking at AI bias and discrimination, with a focus on gender.


About The Machine Ethics podcast

This podcast was created, and is run by, Ben Byford and collaborators. Over the last few years the podcast has grown into a place of discussion and dissemination of important ideas, not only in AI but in tech ethics generally.

The goal is to promote debate concerning technology and society, and to foster the production of technology (and in particular: decision making algorithms) that promote human ideals.

Ben Byford is a AI ethics consultant, code, design and data science teacher, freelance games designer with over 10 years of design and coding experience building websites, apps, and games. In 2015 he began talking on AI ethics and started the Machine Ethics podcast. Since then, Ben has talked with academics, developers, doctors, novelists and designers about AI, automation and society.

Join in the conversation with us by getting in touch via email here or following us on Twitter and Instagram.




The Machine Ethics Podcast

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

coffee corner

AIhub coffee corner: World models

  22 May 2026
The AIhub coffee corner captures the musings of AI experts over a short conversation.

Why the world’s banks are so worried about Anthropic’s latest AI model

  21 May 2026
The finance world’s concern rests on the impressive cyber capabilities of a product called Mythos.

Embracing empiricism – from the lottery hypothesis to creating real-world impact: an interview with Jonathan Frankle

  20 May 2026
Jonathan Frankle discusses empiricism, making an impact, and the legacy of his lottery ticket hypothesis.

A faster way to estimate AI power consumption

  19 May 2026
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.

Introducing ARFBench: A time series question-answering benchmark based on real incidents

  18 May 2026
To resolve system failures, engineers must troubleshoot outages quickly.

Does ‘federated unlearning’ in AI improve data privacy, or create a new cybersecurity risk?

  15 May 2026
As the capacity of AI systems increases apace, so do concerns about the privacy of user data.

Reflections from #AIES2025

and   14 May 2026
We reflect on AIES 2025, outlining a discussion session on LLMs for clinical usage and human rights.

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence