Are you ready for HAL?: 4 questions to ask about AI before launch

Though the fictional HAL supercomputer was first launched to movie-goers greater than 50 years in the past, there are essential classes discovered that AI practitioners can apply at present.


HAL Supercomputer prop from Stanley Kubrick’s 1968 movie, “2001: A House Odyssey.”

Picture: Hethers/Shutterstock

HAL (heuristically programmed algorithmic pc) first debuted within the Stanley Kubrick traditional movie “2001: House Odyssey” (1968). Whereas a part of HAL’s programming required the pc to maintain the actual objective of the mission a secret from astronauts, HAL was additionally programmed to help its human vacationers on the mission by verbally taking questions and directions and in addition offering verbal suggestions with the assistance of pure language processing.

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Extra about synthetic intelligence

Throughout the voyage, HAL skilled logic conflicts when it tried to stability relaying essential data to astronauts in opposition to its directive to maintain mission data secret. The top consequence was a sequence of software program malfunctions that positioned HAL on the trail of destroying the human inhabitants of the ship with a view to safeguard the secrecy of the mission. 

“2001: A House Odyssey” confirmed in theaters greater than 50 years in the past, however is prescient within the questions that loom for organizations as they inject synthetic intelligence into enterprise processes and decisioning. Amongst these questions are:

What’s correct?

In October 2019, Amazon’s Rekognition AI mistakenly categorised 27 skilled athletes as criminals, and in March 2021, a Dutch court docket ordered Uber to reinstate and compensate six former drivers who have been fired based mostly on incorrect assessments of fraudulent exercise that have been made by an algorithm. 

Many organizations enter the AI area by buying an AI bundle that’s already pre-programmed by a vendor that is aware of their trade. However how nicely does the seller software program perceive the particulars of a selected company setting? And if firms proceed to coach and refine their AI engines, or they create new AI algorithms, how do they know once they’re inadvertently introducing logic or information that can yield flawed outcomes?

SEE: Gartner: AI is transferring quick and will likely be prepared for prime time prior to you suppose (TechRepublic) 

The reply is, they do not know as a result of firms cannot uncover flaws in information or logic till they observe them. They acknowledge the issues due to their empirical expertise with the subject material that the AI is analyzing. This empirical data comes from on-staff human subject material consultants. 

The underside line is that firms should maintain human SMEs on the finish of AI analytic cycles to make sure that AI conclusions are affordable—or to step in if they don’t seem to be.

What’s moral?

A big retailer needs a predictive software program that may anticipate buyer buying wants earlier than clients truly make purchases. The retailer purchases and aggregates buyer information from a wide range of third-party sources. However ought to the retailer buy healthcare details about customers to find out in the event that they want diabetic administration aids?

That is an ethics query as a result of it intersects with particular person healthcare privateness rights. Companies should resolve the best factor to do.

The place do people slot in?

Ultimately, human data is the motive force of what AI and analytics can do.

The usual is that AI is cutover to manufacturing when it’s inside 95% accuracy of what subject material consultants would conclude. Over time, it’s doubtless that this synchronization between what a machine and what a human would conclude will drift.

SEE: Deloitte: The highest enterprise use circumstances for AI in 6 client industries (TechRepublic) 

Realizing that AI (just like the human mind) is not all the time good, most organizations choose to have a subject skilled as the ultimate assessment level for any AI decision-making course of.

What limitations will we face?

As we speak’s AI analyzes huge troves of information for patterns and solutions, nevertheless it does not possess the human skill to intuit or tangentially arrive at solutions that are not instantly within the information. Over time, there will likely be work to boost AI’s intuitive reasoning, however the danger is that the AI can go off the rails like HAL.

How will we harness the ability of AI so it does what we ask it to do, however does not find yourself blowing the mission? That is the balancing level that organizations utilizing AI have to search out for themselves.

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