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Deep dive: Creating effective retention strategies

5 difficult conversations and how to have them

Microsoft lays off 3% of workforce while renegotiating partnership with OpenAI

Navigating the workplace as a young product manager

How Stack Overflow is competing with AI – Jody Bailey (CPTO, Stack Overflow)

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

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

Eira Hayward

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