LATEST POSTS

How to build machine learning-based products

BY Olga Kuritsyna on May 26, 2022

In this article, written for product managers, data scientists, and engineering teams we cover some growth areas and ideas on how to achieve more impact while working on building ML-based products. […] Read more »

Machine learning in product discovery - Ha Phan on The Product Experience

BY The Product Experience on April 6, 2022

In this weeks’ podcast episode, we spoke with Ha Phan, Director of Discovery Products at Pluralsight, to develop a stronger understanding of how we can best use ML in product management. […] Read more »

Should you really be using machine learning?

BY Chris Wade on June 24, 2021

Used properly and in the right place, Machine Learning (ML) is an incredible tool to bring value to your product and your users. But how can you use the five product risks—value, usability, feasibility, viability, and ethics—to know if the opportunity is right for ML? […] Read more »

Designing for Cognitive Bias - David Dylan Thomas

BY The Product Experience on April 28, 2021

Monika Turska defines the job of a Product Manager as someone who helps make better decisions, faster. But making the right decisions—whether it’s the ones that we’re actively making, or the ones we’re empowering our algorithms to make—requires a real understanding of the environment they’re being made in. We asked Design for Cognitive Bias author, […] Read more »

Solving Ethical AI Problems, When Algorithms Go Wrong, and the Skills Needs To Work on AI Solutions: Insights From Kriti Sharma

BY Imogen Schels on December 3, 2020 for Prioritised Members

In our final AMA of the year, exclusively for Mind the Product members, Kriti Sharma, VP Product at GfK, shares her AI insights. Watch the session again for real-life examples from Kriti’s awesome back catalogue of AI work and learn about AI trends, tackling ethical AI questions as a product manager, the skills needed to […] Read more »

Machine Learning for Product Managers - A Quick Primer

BY Alexey Kutsenko on August 4, 2020

Currently, there are thousands of products, apps, and services driven by machine learning (ML) that we use every day. As was reported by Crunchbase, in 2019 there were 8,705 companies and startups that rely on this technology. According to PWC’s research, it’s predicted that ML and AI technologies will contribute about $15.7 trillion to global GDP by 2030. It’s obvious […] Read more »

Helping a Machine to Distinguish Toilet Flush From Kitchen tap: a Case Study

BY Dmytro Prosyanko on June 10, 2020

In this case study, Dmytro Prosyanko, Product Manager at McKinsey & Company, Dr. Andrew Pike, Data Scientist, and Danylo Pavliuk, Product Designer at Temper, discuss why effective collaboration between product, data science, and design is crucial for successfully developing next-gen smart tech products. Overview The focus of this case study, co-authored by all three of […] Read more »

Why Machine Learning Products Should be Managed Differently

BY Mark Barlow on January 17, 2020

Machine learning (ML) based products have particular characteristics and challenges, from data quality to counterfactual problems and explainability. What then are the implications of ML products for team structure, focus, and hiring? Data science jobs are increasing at around 30% year on year, and if you don’t already have a data scientist in your ranks […] Read more »

Ground Rules for Applying AI to Product Management

BY Patrick Tsao on January 6, 2020

The hype around artificial intelligence (AI) and machine learning has led to lots of jargon, so that this very powerful technique has become more difficult to understand. The tips below have all helped me, so I hope this article will help product managers to cut through the noise and better understand how AI can fit […] Read more »

Designing Meaningful Human Experiences by Kate O'Neill

BY James Gadsby Peet on November 29, 2019 for Prioritised Members

In this #mtpcon London keynote, Kate O’Neill, founder of KO Insights, considers the question: How can humanity prepare for an increasingly machine, tech and data-driven future? Key Points We need to prepare society for an increasingly tech and data-driven future We must build products that create meaningful human experiences now and in the future To […] Read more »