post

Footer About

Footer Contribute

Footer Get Involved

Footer Links

Mind the Product

Artificial intelligence (AI)

Synthesia becomes the UK’s largest AI product: Lessons for product teams

Guest Post

Does product management only work for tech and startups?

B2B product management

Artificial Intelligence (AI) & Machine Learning (ML)

Building Product Teams

Business Strategy

Data Driven Product Management

Digital Transformation

Diversity and Inclusion

Minimum Viable Product

OKRs

Prioritisation

Product Design

Product Research

Product Development Process

Product Ethics

Product Discovery

Product Leadership

Product Management Career

Product Strategy

Stakeholder Management

🌎 <a href="https://www.mindtheproduct.com/world-product-day/" style="color:#FFFFFF;text-decoration:underline;">Happy World Product Day!</a> Be sure to celebrate product, yourself, and your peers today! 🎉

The best resources for product managers in 2025

Three amazing speakers to learn from at #mtpcon London 2025

Should you specialize or stay versatile in product?

How GenAI has improved GoDaddy’s product experience – Laka Sriram (VP Generative AI, GoDaddy)

Meta scraps third-party fact checking in favour of community notes

Eira is an editor for Mind the Product. She's been a business journalist, editor, and copywriter for longer than she cares to think about.

Eira Hayward

This week’s Sunday Rewind harks back to 2020 and a short series Mind the Product produced on the risks associated with predictive tech, and potential routes forward for product people as they consider how to deal with the ethical issues associated with designing products.
It examines the waning trust in tech companies in the wake of poor performance by predictive tech and the industry’s apparent inability to govern itself. There’s a robust body of evidence to suggest that, of all business variables, trust has the most disproportionate impact on the bottom line.
Product people need to put themselves front and centre in the search for trustworthiness. They can be an immensely powerful and influential community in the ethics debate because they get to decide what a product ends up looking like. One commentator also observes that ethics issues are magnified in AI because of the application of heavy-duty maths that lay people don’t understand and the use of data as an approximation for the real world.
There’s an increase in interest from tech companies in developing codes of ethics or ethics frameworks, but typically most organisations have a lacklustre approach to ethics.
The article finishes with a look at what product managers can do to get started in what is a big and often overwhelming topic:-
Don’t reinvent the wheel &#8211; Look at what philosophers and ethics practitioners have said about the use of technology and its role in society.
Marshal grassroots support &#8211; In general, people want to behave in an ethical way, and to do good, so getting support should not be difficult.
Review how you handle data &#8211; You’ll probably see opportunities to do things in a more ethical and inclusive way.
Codify your standards &#8211; There are a number of published frameworks that companies can use to help put their ethics guidelines into practice
Read the original article: <a href="https://www.mindtheproduct.com/predictive-tech-and-data-ethics-part-1-the-pros-and-cons/" target="_blank" rel="noopener">Predictive tech and data ethics: Part 1 – the pros and cons</a>

core/freeform

AI ethics advice from former White House technologist – Kasia Chmielinski (Co-founder, The Data Nutrition Project)

How Google makes AI work at Enterprise scale – Miku Jha (Director, AI/ML and Generative AI, Google Cloud)

LLM workflows for product managers: 3 key takeaways (Niloufar Salehi, Assistant Professor at UC Berkeley) – ProductTank SF

The future of product management: Insights from ProductTank San Francisco

Product lessons learned making early moves with AI in media: Lindsey Jayne (CPO, Financial Times)

A year with ChatGPT and product innovation: Navigating the AI landscape

How to keep your head about generative AI (when everyone is losing theirs) by Claire Woodcock

What we get wrong about technology by Tim Harford

Product management in the age of ChatGPT by Yana Welinder

How Canva uses AI-powered features to drive PLG

SUNDAY REWIND: Predictive tech and data ethics: Part 1 – the pros and cons

ProductTank Tel Aviv-Yafo

ProductTank Köln

ProductTank Oxford

ProductTank Des Moines

ProductTank Barcelona

ProductTank Bristol

ProductTank San Francisco

ProductTank Madrid

ProductTank Leeds

ProductTank Raleigh

ProductTank Delhi

ProductTank Kathmandu

ProductTank Baku

ProductTank Tallinn

ProductTank Norwich

ProductTank Portland

ProductTank Abu Dhabi

ProductTank Manchester

ProductTank Newcastle Upon Tyne

ProductTank Milton Keynes

ProductTank London

ProductTank Jacksonville

ProductTank Phoenix

ProductTank Ljubljana

ProductTank Belgrade

ProductTank Bologna

ProductTank Edinburgh

ProductTank München

ProductTank Birmingham

ProductTank Porto

ProductTank Heidelberg

ProductTank Paris

ProductTank Hamburg

ProductTank Reading

ProductTank Bangkok

ProductTank Düsseldorf

ProductTank Warsaw

ProductTank Bielefeld

ProductTank Tokyo

SUNDAY REWIND: Predictive tech and data ethics: Part 1 – the pros and cons

Eira Hayward

Read more

Comments