Would a Robot Have Saved SsangYong? Exploring A.I. and Discretion

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Mostly as a result of some very successful tech entrepreneurs’ views, lots of people are quaking in their boots at the thought of what they subsequently believe to be the impending “rise of the machines.” The foremost casualty cited in this dystopia is the loss of jobs, with robots said to be lining up to take all our jobs…

To put the minds of the most fearful at ease, think about how a platform such as YouTube Music struggles to match musical ads to your taste, or how YouTube proper’s video recommendation algorithm is far from effective. Do you mean to say that all the financial resources and leading minds that are at Google’s disposal (the owner of YouTube) can’t get an army of the top programmers to get a simple video recommendation algorithm right?

Every indication is that they can’t, because surely they can find a way to better monetise a good user-experience over monetising the not-so-stellar current user-experience? This question addresses the counter-argument of the user experience deliberately made to leave a lot to be desired, so that there will always be a quick turnaround time in content creation and interaction as the emphasis and a reason to hope for something much better to come…

The point is if Artificial Intelligence doesn’t seem to be viable in a world that’s effectively only driven by computer code, how far are we from a world where robots do indeed take over all our jobs?

Fortunately, even if it was the case that the dystopian rise of the machines was immediately possible, there are people in strategic economic policy-making positions who understand the need to apply discretion. Imagine if the South Korean courts relied solely upon some or other “efficient” A.I.-driven and blockchain technology-regulated robot to make a decision around the once-looming possible liquidation of SsangYong, back in 2015.

The company is now thriving as the fourth biggest motor manufacturer based in South Korea, but would a robot, programmed for efficiency, have opted to save the company? The many possible answers open up the same can of worms that exposes what are essentially an infinite number of permutations any A.I-based system would have to compute. What about some possible factors which nobody, let alone a machine that has to be programmed with all possible outcomes, could foresee?

We’re talking here the likes of something like how the company’s revival plan pushed it into the realms of multinational investors who might just be looking to expand in that particular region, as was the case with Mahindra going on to acquire SsangYong. Would the cold, hard machine, which might very well have some biases programmed into it as part of the decision-making process, “decide” to exercise discretion and determine that a revival was a worthier course of action than liquidation?

Sure, this probably only leads to more questions than answers, because it can also be argued that an A.I. machine system could have been so efficient in its planning of day-to-day operations that it would have avoided any whiff of insolvency in the first place…