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January 07, 2022
My internship journey from galaxies to ethical AI
By: Matthew Chan

Matthew Chan

I'm studying for a PhD at Lancaster University, and my research is in astrophysics. I study what are known as galaxy clusters, which are the largest gravitationally bound objects in the Universe. Essentially, a galaxy cluster is composed of hundreds of galaxies within a ‘small’ volume of space. My PhD project involves applying data science techniques to try to catalogue galaxy clusters and learn about their properties using data collected from some of the biggest telescopes across the world. As part of my studies, I also needed to complete a six-month data science internship within industry.

The Alan Turing Institute offered some internships, and some of those that I found most interesting were with Accenture. So, I applied and fortunately, I was successful! Before I started, I knew Accenture as a large technology consulting company, but I wasn’t aware of how technology consultants would operate on a day-by-day basis. The range of activities and areas that I have been able to engage with have really opened my eyes. Working in a very, large global organisation is not what I expected – there’s a much greater sense of community than I thought there would be. And whatever you need to find out or learn, there’s always someone who will talk to you or will point you in the right direction.

The projects that I worked on, during my 6-month internship, were focused on data ethics and AI. Initially, I was assigned to catalogue the existing assets within Accenture that addressed responsible AI. This task would help other Accenture people quickly find relevant assets for their projects involving data ethics and responsible AI. And these are issues that will come up more and more often as the use of AI increases.

For example, understanding how bias within data could skew the outputs of an AI solution is critical. Otherwise, many businesses that use AI could find that they are inadvertently perpetuating existing biases, such as favouring men over women in a recruitment process. In order to make sure that AI behaviour is ethical, it’s also essential to make it explainable, so that people can understand how the underlying decisions can generate outputs.

That leads me on to another project that I had the opportunity to work on – creating a responsible AI playbook. This served as an internal reference to ensure that all future client projects follow a similar responsible AI framework. In summary, the playbook contained a collection of ethical issues related to data and AI as well as providing guidance on how to address them. This is key, because if businesses get this wrong, it can result in serious consequences and cause reputational damage.

The third project that I worked on was a literature review that focused on investigating the latest thinking around AI fairness. This ensures that we have a good grasp of current developments in the field, which could help enhance the way that we address data ethics and responsible AI.

In addition to working on these projects during my internship, I had a chance to get involved in other ‘side of desk’ activities. For example, I took part in a competition that Accenture organises every year called Cloud Wars. The idea is that participants pick a cloud platform (i.e. Amazon Web Services, Google Cloud Platform or Microsoft Azure) and then work on a data science initiative. I was part of the Amazon Web Services team that delivered a project to help a charity make better use of its data. My contribution was focused on translating survey data collected from a wide range of countries.

My overall impression of the internship? There is always something new to learn and there is always someone available to help you find what you want to know. Furthermore, there is a real sense of community which I wasn’t expecting before I joined, but I have been very happy to discover!

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