The Human Element in the AI Wave

I was reading up a recent post by Bret Greenstein and wanted to expand upon the same.

It is critical to recognize and acknowledge that the success of AI is not going to be based on only the technological advancements in the field; unless a ecosystem of diverse and collaborative skillset of humans work together, AI will fail to live up to its true exponential potential.

In fact, and in order to truly take advantage of AI, we need first acknowledge that there is a synergistic relationship between the humans and AI systems, each unique in their skills that they bring to the table. While machines are best at performing repetitive tasks, handling routine cases, and at quickly analyzing huge data sets, humans are best at exercise judgement, ingenuity, entrepreneurial, and leadership skills to resolve ambiguous and complex cases. The key hence, is to acknowledge the symbiotic relationship between humans and machines and leverage the strengths of both to reimagine and reengineer fluid, adaptive, and transformative business processes.

The classic book entitled 'Human + Machine' has given a very good exposure to the diverse set of human skills that are going to be required to sustain this exponential potential growth.

I am going to share just a sneak peek into some such roles and skills in this new age AI:

? Data hygienist – ensures that not only the algorithms themselves are unbiased, but also the data used to train them must also be free from any slanted perspectives

? Empathy trainers – individuals who will teach AI systems to display compassion

? Personality trainers – individuals who will teach advanced AI systems to be more human like. As an example, the Cortana training team has a poet, a novelist, and a playwright.

? Worldview and localization trainers – individuals who will be tasked to train AI systems on developing a global perspective and make such systems sensitive to and accommodative of cultural variations

? Algorithm Forensic Analyst – are skilled personnel who can help explain the inner workings of complex algorithms. They are able to conduct autopsy on results, when any AI system makes a mistake and understand the causes of the behavior so that it can be rectified.

? Explainability Strategist – are individuals who are responsible for making important decisions on which AI algorithms may be best suited for specific applications

? Ethics Compliance Manager – acts as watchdogs on AI systems to lookout for AI outputs that contradict generally accepted norms of human values

? Context Designers – individuals who take into account a variety of contextual factors, including business environment, the individual users, the cultural issues, the usage environment to ensure seamlessness of AI systems to work alongside humans.

? Machine Relations Manager – function like the HR managers, except that they will oversee AI systems, not human workers, regularly conducting performance reviews of all AI systems

As you can see, and you can certainly read more in books like Human + Machine, the success of AI is truly based on people with varied inter disciplinary skills working together. 

The key to remember is that, in the days of computers, we had to teach ourselves (humans) on how to get used to using a computer (e.g. turning it ON, using DOS, using Microsoft apps, etc.), i.e. humans were trained to use computers; it was unidirectional. Today, and in the days to come, the coexistence between humans and machines has turned the upended the learning metaphor - the machines now have to learn how humans behave and act so that they can be seamlessly accepted in the digital society to coexist with humankind.