The impact of Artificial intelligence on Business Decision Making
In recent years, businesses whether small, medium or big have been relying heavily on the new technological advances namely automation and Artificial Intelligence (AI). The latter has been and is being used in businesses to address various issues and help businesses gain competitive advantages. Its span of influence includes but is not limited to retailing, pricing, management and decision making. In this paper, we are going to focus on the impact of AI in decision making. As Agrawal (2019) put it “Each prediction task is a perfect complement to a decision task”. AI is being used in business decision making because of its ability to process a large amount of data in very limited time and address its complexity, it’s unbiased reasoning (Parry, 2016) and ultimately for AI’s ability to deal with “known unknown” (Metcalf, 2019).
One of the greatest advantages of AI for business decision making is the possibility of processing a huge amount of data and interpret it in real-time. Our little brain is known to being very complex and being able to analyze lots of data, but it is also very prone to overfitting. On the other hand, AI is even better when there is data overload. In the world we are living now, everything we do is being transformed into usable and useful data. Every click we make when browsing the internet; every Facebook like we give; every product we buy online are being recorded for the company in question to give us more targeted ads, or product recommendation, feeds, or just to use for their obscure purpose, things we have no idea are being done with our data. Could our brain still stand this infinite stream of data? I doubt so. This goes without saying that most companies will now try to leverage this powerful tool. Ever wondered why your YouTube homepage is full of videos related to the ones you’ve seen recently? There is a recommender system doing this for every YouTube user, even those who don’t have a YouTube account. Could people do this without AI? Sure, they could but it would take an eternity, because of the enormous amount of data they would have to look at and process by themselves. Thanks to AI’s large data processing advantage, this task can be easily done within seconds or minutes. In the case of YouTube, the AI agent decides by itself, but, in case of a more important decision, like deciding whom to hire or who is guilty, the AI agent would just do the raw job of processing the data and a human decision-maker will have to make the ultimate decision.
Sometimes the data is not just big, it is complex. Financial data, for example, can be big but hardly complex. They are very well-structured. Other kinds of data like voice and text data are complex. There are many subtleties in these kinds of data. That’s where DSS comes in. DSS stands for Decision Support System and it can put forward better and more sophisticated representations allowing more complex states and reasonings to be handled. GDSS, an extension of DSS when “G” stands for Group, “combines communication, computing, and decision support technologies to facilitate formulation and solution of unstructured problems by a group” (DeSanctis & Gallupe, 1987, p. 589). An AI-based decision system can better identify data sets that have chaotic patterns embedded within and are therefore highly complex and difficult to envision (Woolley, Agarwal, & Baker, 2009). For example, manufacturing systems use sensor data to control the running time, failure time of the machines, among other useful data. These are very complex and not human-friendly. Sensor data usually just capture time, acceleration, temperature… and these data only become useful when some patterns are drawn between them. Before AI, human decision-makers would spend lots of time delving into these data to understand them, and their understanding was often partial or inaccurate. Now, they can rely on AI to transform these complicated data into human-readable forms and help them make better decisions.
The biggest threat to fair and inclusive decision making is human bias. We all have it and it’s hard to tackle. Often, when human leaders make decisions, they may serve to extend their control preferences, which they may not wish to relinquish. However, an AI-based leadership decision system would have no such qualms and therefore would focus on effectiveness and logic when generating a decision. The AI system will just look at the data, no stereotype, no background thoughts, unlike humans who have inherent preference. AI can also have bias, but these biases are easy to spot and correct. A study by McKinsey Institute shows that, unlike human decisions, decisions made by AI could in principle (and increasingly in practice) be opened up, examined, and interrogated. To quote Andrew McAfee of MIT, “If you want the bias out, get the algorithms in.” This doesn’t mean that we need to put humans out of the loop. When humans understand and work with the machine, the bias will be reduced and better, fairer decisions will be made.
AI can also help with known unknowns. A known unknown is information whose existence someone is aware of but does not possess. Known unknowns are what drives many scientific experiments, search engine and database queries, business intelligence (BI) and data analytics, among other channels of inquiry. While known unknowns are challenging to humans, a new branch of AI called ASI (Artificial Swarm Intelligence) is tackling this issue and is doing amazingly well. ASI connects humans and computers to achieve greater intelligence and make better decisions. “ASI provides the means for networked individuals to combine their explicit and tacit knowledge in real-time and to work synchronously to make predictions, to assess alternatives, and to reach decisions about known unknowns.” (Metcalf, Askay & Rosenberg, 2019). When enabled by ASI, human swarms form a collectively intelligent system that can outperform traditional methods of dealing with known unknowns, including machine learning, AI. Moreover, ASI enables dozens, hundreds, or potentially thousands of people to combine their insights simultaneously and to successfully reach decisions as a unified system. Emerging research demonstrates that, by pooling all of the intelligence available in a swarm, ASI enables human groups to make surprisingly optimized decisions and accurate predictions about problems that are known unknowns. (Metcalf et al., 2019)
In a world where data is perceived as the new oil, one might think that having lots of data is a blessing but, when you think about it, it can also be a curse. The more the data, the harder it is to analyze thus, without proper tools, it becomes a burden. Businesses need to make lots of decisions; “should we release a new product?” “Should we hire this person?” “should we shut down this factory?” … These decisions are crucial since they can either save the company or kill it. For businesses to carry this burden and change it into a competitive advantage when making decisions, they are increasingly relying on AI. In this paper, we presented four of the many reasons why AI can be a useful hand. First, AI can process huge amounts of data, it is indeed better when the data is big. Second, AI can deal with complexity. The AI tools can pre-process the data, remove the complexity and provide us with simple, straightforward insights that we could use to make better decisions. Third, AI can tackle bias. It has no emotions, no feelings, it just let the data speak by itself. Finally, AI can help human decision-makers deal with known unknowns with the new concept of ASI, which combines humans and machine intelligence into a “powerful combination of many individual minds”. It is no surprise that businesses are racing to adopt AI. Decision making is so vital and AI makes it so easy.
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