Anticipating 2025 – Part Three: Redesigning Artificial Intelligence

Part three of Anticipating 2025 will summarize the third section of the book. This section focused on redesigning artificial intelligence, with a look at six important questions and the exploration of human-machine mergers. The six questions explored in this section are:

  1. Can we create a human-level artificial intelligence?
  2. If so, when?
  3. Will human-level artificial intelligence lead to super-intelligence?
  4. If super-intelligence arrives, will we like it?
  5. Can we upload our minds to computers?
  6. Can we de-risk the arrival of super-intelligence?

Like the first two sections, this section forces us to look at disruption through a different lens. Granted, the path forward is highly speculative, and even the most optimistic scenarios are likely years away from having transformative implications. Nonetheless, it does force us to broaden our lens beyond traditional views. For example, I’ve focused on the automation of knowledge work and all its ramifications, while the authors (Calum Chace, Martin Dinov, and Elias Rut) focus on creating super-intelligence by uploading our minds to computers. They explore a human-machine merger that they see as the enabler of super-intelligence benefits realization. This merger in the author’s view is the only way to avoid creating our successor. So yeah, that’s a little more impactful than automating knowledge work.

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The Second Machine Age and Business Evolution

I just finished reading a new book titled The Second Machine Age written by Andrew McAfee and Erik Brynjolfsson – both from MIT. The book is a must read for leaders everywhere. Its journey offers a view into the potential societal, economic, and business impact of technological advancement in the digital age. Although I am fascinated by each of these, my interest in summarizing this book is to connect their perspective to the future of business. Consistent with my recent disruption theme, the question is: how does the world that the authors envision impact the future of business?

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Cognitive Computing and the Internet of Things

2014 has started with a bang! If this is indicative of things to come – it will be an interesting and exciting year. Two major events usher in our New Year: IBM announcing the formation of the IBM Watson Group and Google acquiring Nest. We’ve heard a lot about the Internet of Things and the growing adoption of Smart Home components. Perhaps not as widely discussed is the emergence of cognitive computing – a space that IBM just made a huge bet on.

In my transformation series last year, I discussed the automation of knowledge work as both an emerging enterprise disruptor, and future enterprise enabler. Cognitive Computing promises to be a major driver of both sides of this equation.  In its simplest form, cognitive computing is technology that allows us to ask natural language-based questions and get answers that support action, smarter decision making, and optimal outcomes. Gartner is weighing in and focused their recent 2013 Hype Cycle on the relationship between humans and machines. The focus – driven by the increased hype around smart machines, cognitive computing and the Internet of Things – is rooted in the belief that the divide between humans and machines is narrowing. Gartner encourages enterprises to look beyond the narrow perspective that only sees a future in which machines and computers replace humans. They see three main scenarios: 1) Augmenting humans with technology 2) Machines replacing humans 3) humans and machines working alongside each other. This is a very reasonable perspective on the likely path. The future enterprise as described through this Blog will use a combination of these scenarios to drive outcomes and transform stakeholder experiences (i.e., customer, employee, citizen, partner, etc.)

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A Closer Look at Transformation: Sense and Respond Systems

Next up in this transformations series is the sixth enabler: sense and respond systems. These systems are critical to the transformation agenda, as most of the disruptive technologies likely to impact the enterprise in the next decade have data at its core. The resulting data explosion promises to complicate information management for most companies. As the speed of business accelerates and the amount of data flowing through company ecosystems expands, the need to sense stimuli and enable a real time response intensifies. Fortunately, rapid advancements in the price and performance of technology make realizing this sense and respond paradigm achievable and economical for a wide range of use cases – but this is arguably one of the most difficult components of transformation road maps.

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