Since the 1950s, artificial intelligence (AI) has been a branch of computer science that deals with the automation of intelligent behavior and has enormous innovation potential. An important aspect of AI is machine learning, which is increasingly talked about today because it has a growing influence on economic processes.

Photo by Yuyeung Lau on Unsplash AI is coming for all companies — not just startups, big tech, and corporates
Photo by Yuyeung Lau on Unsplash AI is coming for all companies — not just startups, big tech, and corporates
Photo by Yuyeung Lau on Unsplash
AI is coming for all companies — not just startups, big tech, and corporates

In the high-tech, telecommunications, and financial services sectors, these systems, based on data analysis and interpretation, are increasingly being used to replace humans. Linguistic AI is already encountered in faster and better translation programs that can follow multilingual conversations simultaneously, making the former interpreter obsolete. In the field of automation, visual…

The basis of AI, Machine Learning or any type of Analytics starts with a data-driven organization

Beginning with AI means you need a proper data culture to start with. AI is not magic, despite what many may still think. Before even thinking of AI, the data needs to be in order. You need documentation, policies, and most importantly a proper data culture. How to achieve this? Continue reading…

Afke Schouten in conversation with Assaad Moawad

This is the first in a series of interviews with practitioners in the field about generating business value with AI. Assaad co-founded the company DataThings in Luxemburg, which is all about translating data into actionable insights. He believes that data can help you better understand your business.


For business readers

Ever heard of model assumptions? What are they? And why are they important? A model is a simplified version of reality, and with machine learning models this is not different. To create models, we need to make assumptions, and if these assumptions are not verified and met, we may get into some trouble.

If these assumptions are not verified and met, we may get into some trouble.

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Every (machine learning) model has a different set of assumptions. We make assumptions on the data, on the relationship between different variables, and on the model we create with this data. Most of…

Five steps to avoid these discussions

I have been in tons of meetings where data and results of any sort of analysis have been presented. And most meetings have one thing in common, data quality is being challenged and most of the meeting time is used for discussing potential data quality issues. The number one follow up of this meeting is to verify the open question, and we start all over again. Sounds familiar?

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It can be different. There are meetings where these discussions don’t take place, or perhaps were started, but immediately taken care of. I have seen and been involved in a few. And…

Don’t start with AI

Many companies want to start with “AI”, whilst this may sound like a good idea for marketing purposes, in order to generate business value from AI I recommend a different approach. Let’s assume you have your data available, you want to start using this data for the benefit of your company. What do you do? Don’t start with a random machine learning project, but consider doing this first.

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Even though the buzzword may have been around for a while, chances are this topic is a new topic for your company. People may not understand AI yet (AI Literacy), and probably…

I often get asked the question, how do I break into AI?

Here’s one way to do it.

Many people want to work in AI, and most that start off their journey aspire to become a data scientist. Apparently the sexiest job of the century. The first thing they do is a Coursera course and then start working on Kaggle competitions, followed by trying to find a job as a data scientist. If this is you, you are one of many, and it will be hard to stand out of the crowd.

Photo by Ashkan Forouzani on Unsplash

Whilst understanding AI through a Coursera course is not a bad idea — you need to educate yourself and become…

Are you responsible for kicking-off AI projects in your organization? And do you need to explain your AI use case to management?

In a previous post, I have written about how I spoon-feed management step by step. Once they understand the gist of AI, and I have an AI use case to pursue internally. It is time for setting up that first meeting to introduce my use case. In this meeting, I keep it simple, I have four key messages I use to explain the use case.

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Message 1: The solution in one sentence

I write down the solution in one sentence. What is it exactly that my solution will do? Going through the process of writing it down one sentence helps me to find the right explanation and…

What is it and why do we all need it?

Not many people truly understand AI, what it is, and what it takes to make it work. Many organizations have started but don’t really know how to make it work and many data scientists are frustrated in their job. We need to do something.

About forty years ago we were in a similar situation. Back then we were in a phase where most people lacked computer literacy. We lived in a time where only a small group of people were technically capable of building computers, creating software, and connecting the soft- and the hardware. Sounds familiar? Back in those days…

Does your manager think AI is just a machine where you put in data and produces an output automatically? And are you tasked with making AI work in your organization? Then this post is for you.

Photo by Lindsay Henwood on Unsplash

I have to be honest with you, you better be in your job for the long run. I hope you are passionate about the company you are working for and are excited about AI. If you do and want to make the investment, then here is a three-step recipe to get your boss to the right level of understanding, and your life easier.

I have written before about the issues many companies face in the adoption of AI. One of the key aspects I speak about is AI Literacy. For me, AI Literacy is a combination of having an understanding…

I am on a mission to make data scientists happy (again)… And at the same time to help companies generating true business value with AI… This is a summary of a talk at the Applied Machine Learning Days at the EPFL in Lausanne Switzerland in January 2020. You can find the talk on YouTube as well.

How I got to this mission

Before the year 2018 I was an unhappy data scientist myself. I was working on projects that were not generating true business value. In my team we missed the right skills and tools for doing the right things. We didn’t know how to build…

Afke Schouten

AI Management Consultant | Senior Data Scientist | Analytics Translator | Teacher. On a mission to help businesses generate true business value with AI.

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