The company “SAS” conducted a study, as a result of which it became clear how ambiguous is one of the most significant technologies of our time – artificial intelligence (AI).
Today, AI solutions are everywhere: they are used in smartphones, they control voice assistants, create news feeds on social networks and direct cars to the desired routes. AI is called the new electricity, but it still remains an undervalued and underutilized technology of our time. This is partly due to the associations that come from science fiction, and partly due to a misunderstanding of the terms “machine learning” and “deep learning”. As a result, the positioning and perception of AI balances between two extremes: it is presented either as a source of limitless opportunities, or as a threat and competitor to people in the labor market.
SAS gathered 12 focus groups. Each respondent was selected by the independent research agency Roots Research and belonged to one of the five categories listed below. Each focus group included 4-5 participants at a time. The session moderators did not directly join the discussions, but motivated the respondents during the discussions and encouraged them to reinforce and expand their views on AI.
- Students: students and recent graduates of specialized universities, about 20 years old. Early adopters of AI solutions in everyday life; they care about how it will affect them
life in the future.
- Data Scientists: Experienced developers and analysts, ages 25 to 40. Have a realistic view of AI’s data collection and protection capabilities.
- Scientists: teachers and professors of specialized universities – this category includes a wide range of experts of different ages. Are optimistic about the capabilities of AI, but have some
concerns about the impact of technology on society, are wary of the ability of businesses to benefit from AI.
- Business Leaders: Senior executives (CEOs and CFOs) between the ages of 40 and 60 who are responsible for managing business processes in their companies. Are enthusiastic about the benefits of AI,
however, we are ready to invest in it only if there is a reliable business plan and proven economic effect.
- CTOs: technical experts between the ages of 40 and 60. Play the role of AI lawyers in their companies, but are skeptical of the solutions on the market in
The study showed that not a single category of respondents gave a clear answer to the question of what is AI – everyone left it in one way or another. A variety of interpretations were offered, with participants describing a wide range of technologies, including those that are not related to real AI.
Scientists were the only group that tried to define in the course of the discussion what AI was, but even they did not reach unanimity on a satisfactory definition. A wide range of opinions turned out to be in the group of data scientists, who, it would seem, should quickly find common points of view, since they work with AI in practice. However, in this category, there were adherents of a wide variety of opinions: for some, AI is a tool for data analysis and decision-making, for others it is an automation tool that, in the long term, can replace humans. There was an even greater heterogeneity of opinions in other categories, but in general, the following pattern was observed: the more experience and knowledge in technology a respondent has, the less fears he has about AI.
The lack of consensus on the definition of AI led to the conclusion that detailed discussions are needed before starting any AI project. The vagueness of the term “artificial intelligence” creates challenges for developers, organizations and even users, and without clear explanations, it can be perceived as anything from a panacea to a threat.
Another important finding from the study was that the solution to the AI puzzle is likely to be to stop looking for all-encompassing definitions. AI can relate to a wide variety of different technologies and case studies and should be defined on a case-by-case basis for each specific project. Recognizing that this or that AI system consists of certain components, honestly and transparently conveying this to the audience is the only way to avoid irrational fears and overestimated expectations from AI.
Despite the disagreement over what AI is, there was strong excitement across all groups about its capabilities. Almost all of the participants are convinced of the positive impact of AI on the economy and believe that it will increase productivity. The respondents from the Data Scientists and Business Leaders categories talked about this based on their own experience. In particular, many cited examples of how AI is already relieving employees from routine monotonous work, freeing up time for more important tasks.
The respondents are confident that AI will help bridge the technical knowledge gap that exists in various industries today. Especially keen interest was aroused by the issue of using AI in healthcare, and it was actively discussed by both those who work in this industry and those who are not related to it. The participants agreed that health services are in dire need of AI tools in the long term. The main role of the respondents is assigned to AI in the field of general diagnostics. Participants from the Data Scientists and Business Leaders categories provided examples from their own practice of physicians relying on an AI solution even when it was at odds with their own opinion. Participants from the student and data scientist categories mentioned that they would prefer to have their medical procedures and surgeries performed by AI. In their opinion, this would reduce the influence of the human factor. However, they stressed that they consider it necessary for such procedures to be accompanied by a qualified medical specialist.
In general, the study suggests that AI, in the opinion of its participants, has a bright future, and in some industries it will especially transform – first of all, healthcare and the financial sector.
At the same time, businesses must take a commercial approach to using AI and clearly define the tasks they want to solve with its help. By thus achieving economic benefits in projects with small investments, it will be easier to convince senior management of the need for wider implementation.