乐播传媒

A discussion with Faculty Director Kai Larsen

Looking to pursue a career in business analytics? With constant advancements in technology and analytical tools, the opportunities for harnessing big data continue to grow鈥攁s does the value of professionals in this occupation. The Leeds MS in Business Analytics prepares students for a data-driven future rooted in ethical business.

Faculty Director Kai Larsen shared his insights on artificial intelligence in today鈥檚 business world and how Leeds is preparing students to harness data and build ethical models that propel businesses forward. 听

Engineering decisions from data

Designed to imitate the decision-making ability of a human expert, an expert system uses data to solve particular problems. While a consultant on Norwegian banking early in his career, Professor Larsen gained exposure to expert systems and the power of using data to make decisions. 听

鈥淚n those early days, we would interview experts like loan processing officers to build 鈥榠f鈥搕hen鈥� statements, and focus on developing systems that built that person鈥檚 knowledge into technology,鈥� said Larsen. 鈥淪o essentially, we were addressing the question of: Can you automate the process of giving loans based on, not the data, but the officer?鈥�

The revolution in analytics that has happened since then, explained Larsen, has been in shifting the focus to collecting, integrating, and analyzing the data about the behavior of consumers before and after receiving loans. Artificial intelligence algorithms, properly configured, take care of the rest.

To Larsen, using analytics in this way means the ability to solve problems in novel ways and fuels efficiency through automated processes. The potential for positive impacts, however, is balanced out by a fair amount of negative possibilities鈥攚hich is why Larsen finds it crucial that analysts are trained to think critically about data. 听

Artificial intelligence and consequence ethics

After years of collecting data from algorithms that were created to behave like experts, professionals now have a plethora of evidence they can examine in order to unearth issues and enhance automated systems.

鈥淲e have an A.I. model of, for example, who deserves a loan or not. That can be torn apart and examined. Well, it turns out that these algorithms鈥攋ust like the humans they鈥檙e based on鈥攁re biased. And that you鈥檝e now automated a biased process.鈥�

Further illustrating the complexity of analytical models, Larsen outlined how a system is comprised of and impacted by both nonexistent and existent data. For example, if loan officers preferred to provide loans to people of a certain race, ethnicity or gender, then the data set and automated system created does not represent the groups of people who were less likely to receive loans.听

鈥淚nitially, a person might argue that not having that data could be a good thing. So now, those groups of people who didn鈥檛 proportionally receive loans can simply apply and the identifying factor that once prevented them from getting a loan, such as their race, ethnicity or gender, can just be omitted from the data鈥攕o the algorithm can鈥檛 figure out what that identifying factor is.鈥�

However, a society鈥檚 systems and all issues within those systems are deeply connected. External influences and circumstances, all rooted in social identities, help construct people鈥檚 individual opportunities and realities. For artificial intelligence, this means that omitting an identifying factor from a data set in order to help right a historical wrong is not that simple.

鈥淒epending on your social identities, you will have had different opportunities in life. Maybe you grew up in a certain area because of your race or ethnicity, which impacts the education you received, what career you have and whether or not you own your house. All of these individual data points, from the products you buy to the car you drive, give hints about your social identities. This makes it very difficult to develop algorithms properly and to prevent any unintentional biases.鈥�

In other words, Larsen explained, the more data you have and the more varied that data, the harder it is to create fair algorithms.

The Leeds approach to business analytics

Training students to not only understand the field of business analytics but also the larger issues in the world is what Larsen finds most exciting about his role. As this discipline continues to evolve, he believes it鈥檚 crucial to incorporate ethics when teaching tomorrow鈥檚 leaders.

鈥淭oday, artificial intelligence is changing the things we can do in a way that鈥檚 creating all kinds of challenging and interesting situations. So, training students well enough that they can chart a course through these issues is to me the exciting part. It鈥檚 no longer just about training them to be able to create artificial intelligence solutions鈥攊t鈥檚 about also training them to do so ethically.鈥�

The Leeds MS in Business Analytics is a ten-month program, where students can choose to learn on campus or online. Shaping students into data experts, the program first teaches how to capture, analyze and translate data sets for actionable insights, before diving into artificial intelligence and social issues.

Fortunately, this grey area is where engineering and social sciences are coming together in unprecedented ways. 乐播传媒 in the program can expect to not only become experts in knowing how to deal with data and drive value for businesses, but they can also anticipate being challenged to think critically about the data and its connections to larger world issues.

鈥淲e鈥檙e not engineers, we鈥檙e not computer scientists鈥攖hat鈥檚 not our goal. Our goal is to teach all of these things in the context of business. With every class the students take, it鈥檚 about learning the statistics, the machine learning tools and the coding鈥攂ut always with a goal toward ethical business. It鈥檚 also a fairly diverse program, which allows for greater opportunities to talk about social issues.鈥�

Business analysts and their growing value in the workplace

By teaching students the skills necessary to go from data to value, the MS in Business Analytics program at Leeds prepares them to create change in a variety of workplaces鈥攆rom healthcare to consulting. With this versatile skill set and the growing opportunities for companies to use big data, business analysts have a bright future in the workplace.

鈥淐an you learn how to take all the data that鈥檚 available right now in a company, figure out what鈥檚 actually important in that data, and create a model in a way that can drive value for a company? That鈥檚 how we train our students. But the actual value comes in when a company makes changes based on what you discover from the model.鈥�

To learn more about Faculty Director Kai Larsen鈥檚 unique insights and his story, read From Norway to Boulder: A professor鈥檚 journey in business analytics.