For decades, the dream of AI has been the development of artificial general intelligence, a machine capable of equalling or surpassing human knowledge in any field. In this Gartner Futures Lab episode, we discuss how, when and if AGI will be achieved and what it means to TI and executive leaders.
In this episode of the Gartner Futures Lab Podcast, host and co-lead of the Gartner Futures Lab, Marty Resnick, sits down with Senior Principal Analyst, Philip Walsh, and Director Analyst, Deepak Seth, to discuss the development of artificial general intelligence (AGI).
Rapid advancements in AI and bold claims from prominent entrepreneurs are fueling hype about AGI’s possibility. AGI, also known as “strong AI,” is the (currently hypothetical) intelligence of a machine that can accomplish any intellectual task that a human can perform. It is a trait attributed to future autonomous AI systems that can achieve goals in a wide range of real or virtual environments at least as effectively as humans can.
Although present AI systems shine in certain tasks, they lack the general-purpose learning, understanding and emotional resonance that define human cognition. Is there more to consider in order to achieve AGI, and is that cognition an important criteria for its successful development? Do we also need to consider the importance of consciousness?
Philip Walsh is a senior principal analyst in Gartner's software engineering practice. He helps software engineering leaders develop and implement strategies to build a world-class software engineering organization. His focus is centered on the evolving role of AI in software development, specifically the impact of AI on developer productivity, developer experience, skills and workforce planning, and the evolving nature of the software engineering leader role and org design.
Deepak Seth is a director analyst with a focus on myriad areas, including, but not limited to organizational and operating models for data, analytics, innovation and AI, data frameworks and processes for responsible, ethical and explainable AI, and data, analytics and AI strategy development and strategy alignment.