More and more companies have been finding ways to incorporate AI and big data analytics into their systems. Implementing effective data preparation is becoming increasingly important to companies to make for better data analysis. In 2018, the global big data market revenue for software and services was worth $42 billion, a figure that Forbes estimates will rise to $103 billion in 2027. However, these companies are quickly encountering the top data science problems and while more players in the industry are using these new technologies, not everyone is able to fully benefit from them because they haven’t got the knowledge to do it themselves. Out of all the companies trying out big data, only 37% have been successful. Given these figures, how can big data improve on its purpose? What role can user-centered design (UCD) play in this process?
Knowing the User
Big data allows computers to compile and analyze big chunks of data and see relevant patterns between them. Artificial intelligence (AI) uses these patterns to predict future outcomes and make human-like assumptions. In a nutshell, these are the fundamental principles of AI-powered data analytics.
Meanwhile, UCD – including data visualization – are all about clear communication. In machines that need to present data to a user for example, it doesn’t matter how information-packed or how aesthetically pleasing your interface may be if the reader struggles to understand your point. If this is the case, then the data has failed to communicate. Jon Geraghty says that in constructing a visualization, it’s important to remember your audience, otherwise known as the user. Thus, in order to improve impact, AI and big data need to incorporate user-centered design into its process.
Incorporating User-Centered Design into AI and Big Data
AI mimics human reasoning, but Wired notes that some AI projects have failed to deliver their intended results. For example, AI algorithms in social media reinforce societal biases, spread disinformation, amplify echo chambers and impair mental health. This is because AI and big data have been put on a pedestal, and are seen as the end-all-be-all of game-changing tech advancements. However, this isn’t exactly true. AI also needs to be paired with human-centered design for it to properly reflect the needs of its users. Both parties need to reach across the table and start working together to create a richer understanding of the user experience (UX). UX and user-centered design combines relevant data with human empathy, which results in a more positive experience for consumers.
There is no doubt that the fundamental principles of UCD can and should be utilized in both understanding and applying the practical benefits of AI, big data, and data analytics. UCD helps with goal-relevance because it’s all about designing products with the satisfaction of human users in mind. In cases where handoff happens-that is, where human intervention is required when AI’s ‘autopilot’ cannot comprehend a certain situation-UCD is necessary to ensure that it happens when it should, and that the process runs smoothly. UCD also prioritizes feedback loops, which help improve AI functions. Without this, a machine would keep on doing what it’s been trained to do, without knowing when and if it has already misinterpreted human behavior.
Additionally, one of the most important benefits of incorporating UCD in AI and big data is the psychological impact. Social media algorithms are designed to be addictive, which leads to obsession and mental health issues. Products that incorporate UCD take into account consumer behavior and the psychological impact these machines have on people.
Recruiting for Tech
Insider New Jersey announced how even the government is catching up in merging tech and user-centered design. The state is interested in leveraging new technology and data to drive social innovation in the public sector. They did this through the launch of the New Jersey Innovation Skills Accelerator, a free online program to train public officials on tech intelligence in order to improve the services being provided for the community.
This and many other examples show how people need to be knowledgeable about both tech and the social sciences in order to reap the full benefits of disruptive technologies. The combination of technology and user-centered design proves how advancements in the tech sector require professionals to be skilled not just in tech, but in fields related to user behavior. The hiring process in the tech sector right now is a direct result of how the world’s most vital industries are scrambling to keep up with today’s disruptive, tech-driven shifts. Not only do companies have to carry out the usual processes for hiring new staff, such as using a company that carries out drug testing in New York, for example, to screen employees, the demand for specialize technical knowledge is a further problem.
Yoss details how hiring for the very best tech jobs involves “rigorous skills validation and qualification process,” which are relevant now more than ever due to the advent of various, interrelated advances. It’s not enough for companies and their employees to be knowledgeable in AI and big data. They should also understand the psychological implications of the technology on intended users.