by Jason Napolitano
As thousands descended upon South by Southwest (SXSW) this year to catch a glimpse of the interactive industry’s biggest leaders, McKinsey and QuantumBlack were pleased to take part in some of the most engaging conversations in data science, design, and artificial intelligence.
As in past years, Artificial intelligence (AI) continues to emerge as a key issue as businesses and consumers wrestle with its perceived value and underlying threats. The conversation at SXSW focused on how we need to rethink our processes, examine underserved groups, and be realistic about expectations of AI. We contributed to discussions in three areas of particular importance: 1) providing inclusive ways to solve complex problems; 2) expanding the skill set of empathy and design with data; and 3) understanding the nuance of AI’s impact.
Providing inclusive ways to solve complex problems
Data scientist Ines Marusic of QuantumBlack joined a women in AI panel to discuss the impact of today’s algorithms on inclusion and fairness. While AI systems have the ability to improve our understanding of complex situations, they can also perpetuate biases, which can lead to decisions that produce unfair outcomes for different races, ethnicities, and genders. The panel talked about the need to ensure that more diverse ways of thinking are represented in algorithms. One way organizations can achieve this is by evaluating the data from society that are used to power artificial intelligence. Today’s machine-learning community has also started to address these emerging issues by redefining the definition of fairness.
According to Marusic, “The hope is that algorithmic fairness will help combat gender, racial, and other forms of bias made by algorithms that make decisions in areas such as loan approvals and resume screenings for job interviews.”
Expanding the skill set of empathy and design with data
During the “Dirty Little Liars: Why Are There Product Failures?” panel, McKinsey partner Mahin Samadani explained that providing impact in the new tech landscape requires us to think empathetically while also scaling insights. Machine learning can augment the design process to help us combine data (the fuel) with empathy (the spark).
Samadani explained a successful approach to gaining insights and scaling empathy-driven design: “With quantified experience design (QED), we explore things from a qualitative standpoint; then, using machine learning, we scale this and identify the opportunities and impact. One doesn’t come before the other: it’s a back and forth, a dialogue. You can get more advanced as the organization gains capabilities, but start with a survey — the original machine learning.”
Expanding on this idea, John Maeda, global head of computational design and inclusion at Auttomatic, underlined the importance of the designer. He stated that designers must push companies to think beyond using AI and data to drive their decisions. Maeda explained that designers today are uniquely positioned to do this because they use empathy, design thinking, and AI (i.e., computational design) to solve important problems.
McKinsey senior partner Hugo Sarrazin echoed this idea in asserting that today’s most innovative businesses also need to rethink what design actually is. “This complex discipline does itself a disservice to call itself just “design,’ which signals only service-level solutions. Perhaps we’ll start to see new ways of describing these multifaceted and interconnected capabilities.”
As Sarrazin explained in “Good design is good business,” a talk between himself and Maeda, design has evolved and taken on different meanings and definitions. And its role and value have expanded to the boardroom by creating impact “at the top.” That means asking the most important questions of businesses: How does design work in your business? How is it not just part of the product journey creation but also integrated into the DNA of the company? How should data drive decisions within the organization?
Understanding the nuance of AI’s impact
We noted that people are developing a much more sophisticated understanding of AI, with more insightful questions asked by the audience during this year’s SXSW panels. The conversation moved beyond AI’s role in efficiency, automation, and cost savings at a macrolevel to its use in more sophisticated areas such as adaptive-learning algorithms and personalized 3-D printing for commerce.
According to McKinsey partner Mehdi Miremadi, people acknowledged the need to be objective about AI’s role. While there are risks (e.g., privacy), McKinsey research has shown that AI can deliver significant benefits to society. Says Miremadi, “AI has been around for decades, and it’s important that we all stay objective. AI will actually bring the creation of new jobs.”
All in all, SXSW 2018 marked a significant step in the maturing of expectations and understanding of what AI can and can’t do.
Jason Napolitano is an experience design director in McKinsey’s Dallas office.