helping you master customer insight leadership

Machine Learning ethics (2) can you design ethical behaviours?

Machine Learning Ethics

Continuing our series of two posts on the topic of Machine Learning Ethics.

In part two of his series on this topic, guest blogger Francesco Corea, moves on to consider moral accountability. How might an accountability, to act in an ethical way, be codified into algorithms or complete machine learning products?

Drawing on sources as diverse as the World Economic Forum & MIT Technology Review, Francesco guides us through some of the issues. he is pragmatic about where there are not yet easy answers, but also helps us to consider the challenge of liability. (more…)

AI ethics (1) Machine Ethics and Artificial Moral Agents

AI ethics

Time for us to consider AI ethics, not just AI developments.

Continuing our focus on themes that emerged at recent Data Leaders Summit, let us consider the AI ethics problems posed by this developing capability.

This builds upon our recent post about the emergence of Product Manager roles within Data Science teams. Another key theme at that event, was the need for Data & AI Ethics. A debate on this at the close of the summit could have run for much longer. (more…)

Audio interviews with Customer Insight Leaders: (4) Gwilym Morrison

Gwilym Morrison interview

Time for another of our audio interviews, with senior Customer Insight Leaders, this time it’s Gwilym Morrison.

A great conversation with Gwilym, who leads Data Science at Royal London Group. So, a good opportunity to complement the data, BI & analytics focus of leaders interviewed already. This time we get to hear the perspective of a Data Science leader. Gwilym has both practitioner & leadership experience and shares honestly from both.

During this interview we discuss his current role and career path, including his transition from analyst to a people leader. After an impressive academic sciencific foundation, his career has taken him across several sectors (including banking & telcos) before arriving at Royal London Group.  (more…)

What is the customer reaction to GDPR telling us about our data culture?

data culture

It’s been several months now since we’ve talked about GDPR, so has it changed your data culture?

Having previously shared 2 blog posts on “how to avoid being bitten on the bum by GDPR“. We also shared posts on a GDPR toolkit & final priorities when nearing the deadline.

In the run up to GDPR, I helped a few firms understand and audit their GDPR readiness. So, 6 months later feels like sufficient time to assess the impact of initial compliance. How has consumer behaviour changed & what does this reveal about businesses data culture? (more…)

Do you need a Data Science Product Manager in your team?

Product Manager

I mentioned in a debrief from the latest Data Leaders Summit, the rise of the Product Manager role within Data Science teams.

This was one of a couple of themes that took me by surprise. Over recent years I’ve become used to hearing about need for more Data Engineers or Analysts to complement Data Scientists. But the focus on Product Managers & product development life-cycles was a new one on me.

However, this was not an isolated incident from only a speaker or two. Both in presentation & personal conversations, many leaders confirmed that had Product Manager roles. So, what is going on? (more…)

Insights from FS firms sharing on CX at #CXCEU2018

Insights from FS firms

This week, I was delighted to attend FinTech Network’s #CXCEU2018 event. It’s the third year running that I’ve been part of this meeting. It brings together FinTech startups & established FS firms, to focus on CX.

As I’ve shared from previous years. this often helps highlight the need for customer insight to guide innovation. Despite the media focus on FinTech or InsurTech startups being all about new technology, analytics & insight can be more important. (more…)

AI misdescription and real world applications from Asia

AI misdescription

In between blogging, from the two events I recommended, let’s return to the challenge of AI misdescription.

As I shared in my review of Tony Boobier’s new book, he calls out the problem of mis-labelled AI. That is analytics or even BI applications being called AI, mainly because it is fashionable.

Below, Tony returns as a guest blogger, to not only confirm that this is still the case, but also call out some genuine AI applications. As a globetrotter, who have previously reported for us from Vegas & Chile, Tony has had the opportunity to see first hand AI applications around the world. (more…)