It is common to see technologists put () technology into a box and wax lyrical about their vision of how it will impact humanity. Elon Musk made headlines when he publicly stated that , in his opinion, posed a significant threat and was in need of regulation, going so far as to call it a “fundamental risk to the existence of civilisation”. Meanwhile, Mark Zuckerberg called such warnings “irresponsible”, and accentuated the benefits could provide in saving lives through medical diagnoses and driverless cars.
It is important to bear in mind that the form of being discussed by Musk and Zuckerberg relates primarily to that has ‘human level’ cognitive skills, otherwise known as AGI or ‘Artificial General Intelligence’. Despite impressive progress in a range of specialities (from driving cars to playing Go), this technology is by no means imminent.
is in use and not science-fiction
What current debates tend to ignore is that is something that’s already in common use by many in a business context today, and that the associated risks are not about whether it will leave us all in devastation. Instead of worrying about such catastrophic scenarios, we should focus our energies on the very real risks posed by this technology in the here and now if it is used incorrectly. These dangers can include regulation violations, diminished business value and significant brand damage. Though not cataclysmic in their impact on humanity, these can still play a major role in the success or failure of organisations.
Artificial Intelligence vs. Artificial Intelligence
As a refresher, not all is created equally. comes in two flavours – Transparent and Opaque. Both have very different uses, applications and impacts for businesses and users in general. For the uninitiated – Transparent is a system whose insights can be understood and audited, allowing one to reverse engineer each of its outcomes to see how it arrived at any given decision. Opaque , on the other hand, is an system that cannot easily reveal how it works. Not unlike the human brain, any attempt to explain exactly how it has arrived at a particular insight or decision can prove challenging. […]