AI and Machine Learning for Business

Dialectic Book Club: AI and Machine Learning for Business

The Dialectic Book Club recently explored one of today’s hottest topics, discussing Artificial Intelligence and Machine Learning for Business by Steven Finlay, a practical and concise overview geared to managers and business people.

Finlay is a data scientist with a Ph.D. in predictive modelling, who specializes in developing machine-learning solutions in big data industries, including the financial sector.

The book begins with the basics, providing easy-to-absorb definitions of machine learning and AI and then explores the value of machine learning and how it works. It provides insights on building a predictive model and how to use such a model to make decisions, as well as ethical implications.

Dialectic team takeaways:

  1. In the short term, machine learning will add jobs, rather than suppress them.
  2. Algorithms can be biased or even racist… if the people who create them are.
  3. Algorithms are fantastic tools for analyzing vast amounts of data and making predictions about the world — such as sales forecasts — but humans are still needed to interpret and act on those predictions.

Also see our advice on getting your workplace machine-learning ready: Machine Learning, AI and Change Management: 3 Ways Leaders Can Prepare Their Organization for Success.

The Dialectic team regularly meets to discuss books that contribute insights to our work designing e-learning, organizational change and customer experiences. Next up, we’re reading Cathy Moore’s Map It: The Hands-On Guide to Strategic Training Design.

Don't Make Me Think, Revisited Book

Dialectic Book Club: Don’t Make Me Think, Revisited

Introducing the Dialectic Book Club

The Dialectic team regularly meets to discuss books that we collectively read for insights into our work designing e-learning, organizational change and customer experiences.

“We read and learn together because it is our job to educate people, and those same skills can – and should – be used to continually educate ourselves,” explains Aaron Barth, Dialectic founder and president. “We always want to be innovative and be on the cutting edge of what is happening in research, design, and technology. So we read things that will keep us there and we use our learning design skills to teach ourselves new things.

“It’s about building capacity across the organization and deepening our unique integrated approach. We all read the same books regardless of our role and learn about each others’ crafts. Since we work in a integrated way – where everyone is involved to some extent at each phase of a project – that delivers superior value and outcomes to our clients.”

Don't Make Me Think, Revisited Book

Recently the book club dove into Steve Krug’s Don’t Make Me Think, Revisited: A Common Sense Approach to Web And Mobile Usability, which is regarded as the bible for user experience (UX) and user interface (UI) design. It’s an engaging, fun read packed with practical advice for intuitive navigation and information design, based on Krug’s 20+ years of experience as a top usability consultant.

Here are some of our takeaways:

1. If it can’t be self-evident, it needs to be self-explanatory
Krug explains that users should be able to navigate websites or apps without thinking about it. This is his first law of usability – and it’s one that we embrace in all of our designs.

2. Omit needless words
Getting your message across with less words reduces mental clutter and is more
straightforward for your audience (h/t to Strunk & White, The Elements of Style).

3. The myth of the average user
There is no such thing as the ‘average’ user. As Krug explains, “All web users are unique and all web use is basically idiosyncratic.” This is why it is so important to test your digital products with as many different people as possible.

Next up, we’re reading Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies by Steven Finlay – stay tuned!