AI has immense potential. It can improve our productivity and also our predictions and decisions, which in turn can help reduce disparities. We all have unconscious biases that influence our choices and actions. It can be hard to understand how we’ve arrived at them and whether biases have played a role. Because AI is programmed and can be audited and changed, it can theoretically help us be more accurate and fairer.  But AI is built with data that has been generated from databases of existing information, such as images, texts, and historical data, so our biases become built-in. Its effects on marginalized groups are often unrecognized even as they are perpetuated, because the technology appears to be objective and neutral. Our report on AI research outlines what scholars have found about how AI can contribute to inequity and what can be done to mitigate it. 

It's tempting to think that an inclusive approach to analytics is just an add-on to a day-to-day job, or worse, isn't profitable. But those are all just myths, say GATE's Sarah Kaplan and Lechin Lu. Gender Analytics is a process to embed insights about gender and its intersections with race, ethnicity, disability, sexual orientation, Indigeneity and other factors to create inclusive product, service and policy design. Despite having a potentially significant impact on society, the idea of inclusive analytics is often misunderstood, though it’s recently risen to prominence as companies prioritize equity and diversity not just in their talent management but also in how they go to market. And there’s a significant upside to the shift: Applying a gender and inclusion lens to product and service development could result in new opportunities for businesses.

It would be difficult to find a field today where AI is not involved in some respect. It has become so ubiquitous that some researchers have suggested it is a new type of infrastructure. Rather than being physical and visible like roads, AI is often invisible, but it is nevertheless a moderator of social relations and organizational practices and actions — including the distribution of power. Social relations and values have long been reflected and reproduced in technology, and AI is no exception. But this also means that the enduring bias, discrimination and inequality that are deeply rooted in society may also be deeply rooted in this technology.

Everybody wants to generate breakthrough ideas. Few people know how to do it. Conventional practice is to pick a vague challenge (“We need innovative ideas!”) and then randomly brainstorm in the hopes of stumbling onto the next Spotify or Slack.

Today, AI is used by organizations across many sectors for a variety of purposes, from hiring employees, to assessing risk, to making investment recommendations, to recommending criminal sentencing. However, it is well-known that social relations and contexts are reflected and reproduced in technology, and AI is no exception: it has the potential to reinforce underlying biases, discrimination, and inequities. Although AI can be used to benefit marginalized groups, a concerted focus on equity in AI by businesses and governments is necessary to mitigate possible harms. Here we provide a resource for scholars and practitioners for viewing AI through the lens of equity, with the objectives of synthesizing existing research and knowledge about the connection between AI and (in)equity and suggesting considerations for public and private sector leaders to be aware of when implementing AI. The key Insight: AI is a double-edged sword, with potential to both mitigate and reinforce bias.

Gender Analytics is a methodology that can be useful both in creating innovation insights that improve impact and in avoiding downside risks, and it should be embedded into everything an organization does. It’s not just an evaluation tool to analyze retrospectively what impact your policy, product, service or process has had. It’s not just a nice-to-have feature you might discuss from time to time. This is something that can shape how you strategize, plan, innovate and serve customers.

Entrepreneurship is a key path to job creation and economic growth in the modern economy, yet women and minorities remain underrepresented. Research to date has documented some “supply side” factors showing that women and/or minorities are less likely to enter entrepreneurship and some “demand side” factors highlighting the struggle these entrepreneurs face in getting funding and other resources. This report underscores a number of debates and controversies in the entrepreneurship literature which are highlighted below along with a roadmap for a future research agenda in gender, race and entrepreneurship

In moments of crisis, companies quickly shift their attention to survival. The COVID-19 pandemic is no exception. Under these circumstances, businesses are scrambling to cope with employee safety and enforced shutdowns, among many other challenges. So it may seem misguided to focus on corporate social responsibility (CSR) now. But, in fact, there might be no better time. Resolving these trade-offs can be a source of innovation.

Trade-offs, conflicts, and challenges, however, can be the source of innovation and transformation. Companies can develop explicit and coherent plans for addressing the tensions created by trade-offs. The stories of two large, well-known organizations, Walmart and Nike (as well as Levi Strauss & Co., mentioned below), show the ways that well-known organizations with varied stakeholders manage trade-offs. This is not to glorify or vilify them, but simply to show how frequently interests and agendas can conflict and highlight the kinds of difficult decisions that arise most often in today’s globalized economy. Coping with stakeholder trade-offs forced Nike to come up with less toxic glues and more environmentally friendly materials for its shoes and Walmart to pressure suppliers to change both products and their packaging to reduce waste and the environmental effects of shipping.

In turbulent markets, it can be hard for established companies to choose new strategic directions. But by rethinking the past and present and reimagining the future, managers can construct strategic narratives that enable innovation.

Most companies invest a significant amount of time and effort in a formal, annual strategic planning process — but many executives see little benefit from the investment. One manager told us, “Our planning process is like a primitive tribal ritual — there is a lot of dancing, waving of feathers and beating of drums. No one is exactly sure why we do it, but there is an almost mystical hope that something good will come out of it.” Another said, “It’s like the old Communist system: We pretend to make strategy and they pretend to follow it.” Management thinker Henry Mintzberg has gone so far as to label the phrase “strategic planning” an oxymoron. He notes that real strategy is made informally. Our own research on strategic planning supports Mintzberg’s observation: We found that few truly strategic decisions are made in the context of a formal process. But we also found that, when approached with the right goal in mind, formal planning need not be a waste of time and can, in fact, be a real source of competitive advantage. Companies that achieved such success used strategic planning not to generate strategic plans but as a learning tool to create “prepared minds” within their management teams (to paraphrase Louis Pasteur).