In The Age Of The Smart Machine : The Future Of...
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The world of work is changing at an unprecedented pace largely driven by mega-shifts (e.g., datafication, personalization, virtualization, augmentation, cognification, mobilization, etc.,) and their combinatorial and interdependent relationships. Artificial intelligence is already present in many aspects of our lives (planning our daily commute, ridesharing, voice and face recognition) and the predictions for future applications abound. And while there is considerable debate on the promises and risks of machine intelligence, there is no doubt that it is advancing rapidly.
Knowing that what can be automated will be automated gives significant importance to what makes us uniquely human: curiosity, humor, empathy, creativity, wisdom, and passion. These are the things that will add value in the future of work. Additionally, the capacity to learn, unlearn and relearn at a rapid pace will be critical. What better time to consider how advances in scientific discoveries made possible by smart machines, such as functional brain imaging, can be applied to human development We believe that advances in Mind-Brain discoveries can support our evolution and increase the probability that a collaboration between humans and smart machines will bring out the best in both.
To address these important questions, we propose three mind-brain principles that apply to everyone responsible for navigating the unprecedented change that marks this moment in history. Following each principle is a set of questions that prompt you to consider and perhaps adjust practices that support being more fully human in a smart machine age.
Our work and life practices are largely inconsistent with what we know about optimal brain functioning. The use of smart machines and technology has increased exponentially in the last few years with increasing reports of addiction to devices, and almost non-stop connection. 
Our mindsets are powerful and malleable. The pace and complexity of change driven by technological mega-shifts and smart machines demands a conscious approach to learning and support for neuroplasticity in the context of learning. Neuroplasticity, our ability to alter neural structures and the very physiology of the brain, is a fact. We can use our mind to change our brain, develop our mindset and create new options for thinking, performing, and relating. Every time we learn and stretch our minds to include new perspectives we create new neural connections. Conversely, left unexamined our implicit habits and patterns of mind are likely to be reinforced making change more difficult. Yet few contemporary approaches to developing leaders focus on growing mindsets.
Early on, it was popularly assumed that the future of AI would involve the automation of simple repetitive tasks requiring low-level decision-making. But AI has rapidly grown in sophistication, owing to more powerful computers and the compilation of huge data sets. One branch, machine learning, notable for its ability to sort and analyze massive amounts of data and to learn over time, has transformed countless fields, including education.
It is clear that a lack of trust in AI outputs is an issue for a number of respondents. However, these reservations could be more of a reflection of the lack of understanding of how these systems work. An alternative view is that AI and machine learning can potentially increase the credibility and accuracy of insights rather than detract from them. This rigor is due to the fact they arrive at conclusions based on a larger number of data sets, rather than an individual probing a single set of data and potentially introducing their own biases into the equation. It is therefore likely that smart machines could undertake data-driven tasks with greater accuracy, consistency and time-efficiency than humans. 59ce067264