Interview with Nadja Keidel, Expert data scientist, Zühlke Engineering AG

In this interview Nadja Keidel (Expert Data Scientist at Zühlke Engineering AG) gave us answers how she became a coder, that there is a major difference in ‘coding’ and ‘programming’ and why we don´t have be afraid for the future. Enjoy reading.

Nadja, you are a data scientist and an R & Python coder for the Zuehlke Group. How did you get into coding and what makes it exciting for you?
The first time I faced a coding task was during an introductory lecture as part of my mathematics degree. We had to write a program that would convert the classic ‘Hello, World!’ message into ‘Hello, Nadja!’. Everyone starts small (laughs). During my studies, the focus was on the languages R & MATLAB. Python was added into the mix later.

I went on to learn that there is a major difference between ‘coding’ and ‘actual programming’. Or, to put it another way: code is a program that is running. Actual programming requires much more skills, as it consists of creating a readable structure and well-implemented logic. You tailor your approach based on best practices such as clean code and a core factor of success is collaboration. You constantly show, review and improve the codebase – this is in fact as important in machine learning projects as in every software development initiative. This is something I learned while working in the industry, particularly in exchange with my software developing colleagues at Zühlke.

What fascinates me is that the ability to program opens a new world to you – it’s like learning a foreign language. You suddenly have a way to see behind things previously concealed. What’s more, programming is a discipline where you see the results immediately. That is very satisfying.

There’s also a certain beauty about a line of code. It’s like in mathematics: a good proof is clear and understandable, and you create a little ‘Eureka’ moment. You experience this sensation in programming, too, which is both fun and requires you to be more creative than you might think. Again, it’s like learning a foreign language: nobody is keen to read a text consisting solely of long, complicated sentences. We prefer clear, logical statements.

One of the fields you focus on is machine learning, quite an exciting subject, which is followed by many questions about the future, e.g. machines replacing some occupations. In your opinion, how will AI change the professional world/society?
As I see it, we’re right in the middle of a radical change right now. And like every new technology, the initial focus is on exploring its various benefits, challenges and limits. In the process, we learn what works and what doesn’t. I think the greatest challenge lies in changing the way we think. In using machine learning algorithms, we are leaving behind the world of absolute numbers and entering one of probabilities. Up to now, we have been able to rely on a computer giving a right or wrong answer. This is no longer the case, as a machine learning algorithm does not deliver an absolute value and is never 100% correct. This is why we need to be more critical in our thinking, and why it is crucial that those working with these technologies bring in a great deal of personal responsibility. I believe it is extremely important that we face up to this challenge and actively create the transparency that is required. Everybody should have at least a basic awareness of how machine learning works – and where its limits are.

Nowadays the future is often described in a negative manner, there is a lot of uncertainty about future technology. Can you offer some reassurance?
Behind every technology are many different options for using it, and behind those options are people who can make a difference of whether it is used in a meaningful way. In my opinion, the worst scenario would be to entrust the knowledge about a certain type of technology to a small group of insiders. Knowledge is power – that isn’t going to change any time soon. I want to build on the previous statement here: we have to break out of the comfort of accepting things without questioning them. This is no radical new concept. Back in history class at school, for example, we were told to always check, and support statements and facts based on multiple sources. Critical thinking, a healthy amount of scrutiny and not blindly accepting everything as the truth: these are already the key pillars of an enlightened society – and this will continue to be the case in the future when implementing new technologies. Then, we will also be able to benefit from the many advantages and opportunities provided by these new technologies.

How can AI improve the future of humanity and what are some sectors where this is already the case?
Assuming they are used sensibly, these types of technology could present a huge opportunity in, say, medicine. We have the chance to benefit from highly personalised medicine, which from the patient perspective is certainly desirable. If I become ill, I receive treatment that is tailored to me and my body. Other examples include projects that use algorithms to scan X-rays to identify certain disease patterns or to make triage simpler for stressed doctors in emergency rooms.
There’s also a current topic in journalism which is exciting: Associated Press (AP) is now creating automatically generated reports, such as for business performance (quarterly figures) and sports results. This enables AP to use AI to publish reports on various companies and marginal sports, which makes it easy to inform readers about how their favourite soccer team did in the fourth division. Previously, you would have had to assign a reporter to something like this for half a day. With less routine work to do, journalists can use their time to investigate in more essential issues. The idea is tempting as people can be released from their dull routine work and focus instead on exciting or important topics. This desire isn’t confined to any one industry, is it?

Finally, something a bit more speculative: In addition to being able to address exciting, important topics, this could also be our chance to benefit from more free time. What could we achieve with the time we save if AI takes care of many or all the routine tasks, we’re currently juggling day by day? Perhaps society will change to the extent that we no longer must spend as much of our time working as we do today.