The following post is an excerpt from my book ‘Designing Human-Centric AI Experiences’ on applied UX design for Artificial intelligence. — I’m a stickler about having Chai and biscuits in the morning. Every week I go to the neighborhood grocery store to buy a regular packet of Britannia Marie Gold…

The following post is an excerpt from my book ‘Designing Human-Centric AI Experiences’ on applied UX design for Artificial intelligence. — Building AI products is technical but also requires creativity. Popular culture depicts people who work in technology as science and math nerds with low EQ. Characters like Steve Urkel…

The following post is an excerpt from my book ‘Designing Human-Centric AI Experiences’ on applied UX design for Artificial intelligence. — An organization is essentially lots of people and machines working together to achieve a particular outcome — different teams and departments in an organization work towards specific objectives that…

We usually think of intelligence as a quality that individuals possess. However, many of our largest and most complex problems are often solved by groups of individuals. If we think of intelligence as an ability to solve problems, groups can also act intelligently. We call this intelligence ‘Collective intelligence’ —…

The entire world is organised into systems. Be it an ecosystem in the forest, nations, markets, communities, governments, or companies. We all form a part of different systems at different times in our life. …

Adam Smith’s idea of the division of labor talks about allocating roles based on relative strengths. It is primarily targeted towards the division of physical labor. Computers and AI making predictions enable a cognitive division of labor between humans and machines based on their respective cognitive strengths. While machines are…

When working with tech teams, your job is to help your engineers make great user-centred decisions. Designing ML systems is a creative process for its programmers too. Getting too prescriptive too quickly can inhibit the creativity of your engineering counterparts. Trust them to use their intuition, encourage experimentation and user…

In traditional software systems, outcomes are discrete and the creators are aware of the behaviour of these systems (rigid set of instructions). AI/ML-based systems bring a fundamental shift to this way of thinking where instead of programming a system to do a certain action, it’s creators provide data and nurture…

Prototyping for ML systems is especially hard. If the value of your product lies in using user data to build a personalised experience, a prototype with dummy data wouldn’t feel authentic. Also if you have a fully built ML system, it might be too late to make any meaningful changes…