IIC Journal of Innovation 11th Edition | Page 55

So, you think you have an AI strategy? Think again. I NTRODUCTION  Popular press, media and even companies tend to portray the future of AI from one of two dominant world views. From a utopian point of view, where AI brings humanity new ways of achieving exponential benefits to economies of scale, productivity and safety, so the implied strategy is “build it and they will come.” From a dystopian point of view, though, AI will make irreversible immoral decisions for mission critical situations, so the implied strategy is “stop it before it takes over the world.” The fragmented thinking regarding plausible systemic risks and benefits for companies, consumers and everybody involved has resulted in AI becoming a controversial topic. Furthermore, the rapid evolution of AI and its convergence with other technology platform ecosystems such as 5G, Blockchain, AR/VR, IOT, Fog and Cloud are driving and shaping new ways for people to live. This next evolution is often referred to as Ambient intelligence or the 4th Industrial Revolution and has resulted in many open questions, such as:    are conditioned on factors, such as impact to environment and society? In what ways might an AI strategy be adapted to be resilient or to thrive under these conditions? In this short overview, we argue organizations will increase the expected value of their investments in AI technologies, products and services by adapting their technology strategy to include the social impact of AI. More specifically, we assert an AI strategy should not just be about technology, but it should also be about integrating open strategy and design thinking processes and practices. These activities should proactively include citizens’ perspectives and participation to gain direct insights and feedback on the plausible systemic risks and benefits of AI technologies before, and not after, they are deployed into their respective community. Secondly, we argue organizations should adopt new analytical methods and techniques deliberately designed to characterize the social impact of AI. These approaches should characterize the impact of AI to factors such as environment, energy and society (ethics, economics, gender, culture, language). Regardless of whether an organization is making mobile apps or autonomous vehicles (AV), we assert they stand to gain more from their AI strategy by expanding it to include the social impact of AI. What is the social impact of AI, really? How might we characterize the plausible systemic risks and benefits of AI before, not after, it is deployed into a community? To what extent does an organization’s AI strategy comprehend plausible futures where the adoption of AI technologies, products and services First, we provide a brief background on our motivations, the opportunity space, and a sampling of existing initiatives exploring social impact of AI. Next, we walk through an example of “Social Impact Factor Analysis” - 51 - June 2019