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Building the Brains of the Robot

by | Aug 29, 2019 | Artificial Intelligence

Every time we talk to Alexa, Siri, Google, or Cortana, we are building the brains of the robot.

Whenever we speak to these devices, we are imparting tiny pieces of human intelligence, and over time, with the right kind of AI learning software, it will be possible to build the kind of foundational base of knowledge needed to operate our robots in the future.

Granted, we are still at the “chisel-on-stone writing” stage of this transformation, but our verbal exchanges are fueling the early reservoirs of human intelligence that will be needed to power the brains of our robots over the coming decades.

The robots, I’m referring to, may be drones, driverless cars, or actual robots, but an incoming stream of intelligence is what will be needed to separate the blind, order-following robots of the past from the emotionally-perceptive, multisensory bots that will be a common site in our future.

In many situations, the robot itself will begin to disappear, and over time will morph into forms of automation that we no longer consider to be associated with robotics.

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How will we know if future robots are making good decisions?

The Ethical Robot Dilemma

How much authority will future bots have? Will they be given the authority to keep alcohol away from alcoholics, cigarettes away from minors, and turn off devices when kids should be doing their homework?

Will the same bots that serve as your personal trainer and image consultant also be given authority to change your diet, schedule doctor appointments, and arrange social engagements?

Will they be given authority to sign for certified mail, to fill a prescription, hire an exterminator, or care for a baby?

Could we also go down the dark side of robotics and direct them to terminate a dictator, rebel leader, or anyone else who may stand in our way?

Will bots be used as the intermediaries in drug deals, human trafficking, and arms shipments to keep the principals at a safe distance?

Will autonomous bots have their own bank accounts and also be required to pay taxes? Could community bots be organized like a foundation and evolve into the biggest tax haven of all times?

In the future, will you allow a robot to give you a haircut? How will you know the good bots from the bad ones?

Isaac Asimov’s “Three Laws of Robotics”

The thinking behind Asimov’s Three Laws of Robotics first started taking form in his 1942 short story “Runaround,” but he had mentioned some of his thinking in a few earlier stories.

In his “Handbook of Robotics” published in 1958, Asimov’s “Three Laws of Robotics” became official:

  1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
  2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
  3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

While the laws seemed very visionary and formed a cultural meme around the ethics needed for the coming age of automation, they are simply not adequate for the nuanced capabilities and behaviors we are beginning to see in today’s devices.

At the same time, Asimov was driving the first stake in the ground for machine ethics, a field that hadn’t even been invented yet, and should be commended for his farsighted approach to the human-machine relationships that we will be wrestling with for decades to come.

Futurist Speaker Thomas Frey Blog: Asimov’s Three Laws Of Robotics

Our relationship with robots is changing. How will we know if they truly care?

Failsafe Mechanisms

If machines are using our conversations to add to the overall intelligence of robots in the future, they will also need to protect our privacy.

If a robot knows everything about me, then it will know our credit cards, bank accounts, and passwords. That level of intrusion into our lives becomes a very dicey issue because too much transparency means we lose our ability to own things, and ownership is a foundational principle upon which our society works.

Does the protection of privacy has become a “new law” required in every future robot operating systems?

At the same time our robots need to understand our preferences. What kind of products do we normally buy? What food do we like, who are our family members, friends, pets, what brands do we prefer, what forms of entertainment do we enjoy? Every piece of information helps streamline our transactions and reduces the amount of time invested in every accomplishment.

If we send our robot to the store to buy groceries, how will we empower it to select the right products?

The Economics of Automation

Our economy is based on people. Humans are the buying entities, the connectors, the decision-makers, and the trade partners that make our economy work.

Without humans there can be no economy.

Generally speaking, when a person buys tools, it increases their capability, and by extension, increases their value as an economic entity.

When a person buys a computer and becomes proficient at using it, this added piece of digitization increases their capabilities, their earning power, and their sphere of influence as a consumer. In general, people with computers earn and spend more than people without computers.

Similarly, people who own cars, homes, and businesses tend to earn and spend more than people without them. Ownership and control becomes part of our personal toolbox, a toolbox that gives us additional capabilities and thereby adds to our economic contribution.

Since the capabilities granted by owning a computer connected to the Internet can be far more scalable than owning a car or home, its influence upon economic theory has been largely underestimated.

We will encounter similar underestimations as we combine the scalability of Internet-connected automation to the capabilities of a person in the years ahead.

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How long before your best friend is a robot?

Final Thoughts

Competing WITH robots is far different than competing AGAINST robots. When we add machine skills to the resume of an individual we end up with a far different equation.

So the coming decades will be far less about humans competing against machines and far more about how we can leverage them to our advantage.

For this reason, it’s imperative that the tech companies formulating these future “brains” get it right. We will need to trust our machines, and trust the decisions they make.

We are still a long way from creating Hollywood style robots with an emotional mind capable of making value judgments that we feel comfortable with. But we are very close to leveraging machine capabilities in far more interesting ways.

Machine-based automation will revolutionize our world every bit as much as our computers already have.

What cannot be lost in this discussion is the need for a rapid transitioning skill base where we quickly identify the gaps and train people to fill them.

Machines can become our greatest asset or our greatest liability. It’s up to us to decide which will dominate.

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