What is Artificial Intelligence?
According to Investopedia, Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
The benefits of AI cut across various Industries, with AI-influenced GDP growth predicted to hit $15 billion by 2030. As the numerous benefits of AI continue to increase, so also do the risks. This article will address the risks of artificial intelligence, and how to mitigate these risks.
What Are the Risks of Artificial Intelligence?
In March last year, SpaceX founder and Tesla founder, Elon Musk, gave a warning: “Mark my words,” he said, billionaire casual in a furry-collared bomber jacket and days’ old scruff, “AI is far more dangerous than nukes.” As if that was not enough the late scientist Steven Hawking said, “Unless we learn how to prepare for, and avoid, the potential risks,” he explained, “AI could be the worst event in the history of our civilization.” Let us take a look at some of these risks;
- Job Automation
It no longer is a discussion of if Ai will replace jobs but when and to what degree. Many industries that perform repetitive tasks are the first hit in this ever-expanding AI wave. As AI becomes smarter and more dextrous, tasks that require fewer humans will be decimated. It doesn’t stop there even professions requiring graduate degrees aren’t immune to AI displacement, as AI is already being used in Medicine.
- Lack of AI use traceability
A lot of workers in Industries use unapproved Software applications at work. Oftentimes, this isn’t done with bad intentions but to increase productivity. Departments may opt for more affordable, cloud-based systems including an AI component without Risk Management and IT being in the know. This connotes a risk to digital security and a possible violation of data privacy.
From a risk management view, Using a risk universe allows us to track, assess, prioritize, and control AI risks, this is rendered impossible when workers use un-approved Software on company devices.
- Program Bias widening societal inequality
AI learns from the dataset on which it is trained and depending upon how this or who compiles this data set, there is potential for such dataset to reflect the assumptions or biases of the said compiler. These pre-defined biases can then influence AI decision-making.
- Autonomous Weapons
Like Elon Musk said “AI is more dangerous than Nukes” Of course not everyone agrees, but think for a second, what if AI actually decides to launch nukes, or more realistically someone manipulated an AI dataset, to launch missiles? These are both very dangerous risks and are alarmingly possible.
- International Stock Market Instability
There are currently many AI bots being used to “trade” on the international markets, how do they do it? Algorithmic trading. This type of trading occurs when AI, executes trades based on pre-set instructions. These AI can make high-volume, high-frequency, and high-value trades that can lead to big losses and extreme market volatility.
This volatility can lead to very huge losses, panic buying and selling, and the probable collapse of financial markets.
How to Mitigate these Risks
The only way to mitigate the ever-evolving risk is to provide some sort of regulation when an AI system is designed with fuzzy algorithms, and machine learning allows the decision-making to refine itself, Who is held responsible? Elon Musk once again provides some valuable insight here,
“I am not normally an advocate of regulation and oversight — I think one should generally err on the side of minimizing those things — but this is a case where you have a very serious danger to the public,”
The following Key systems should be put into consideration when developing/using AI systems;
- AI systems should include clear data set design documentation.
- The control of AI should take priority over algorithms and efficiency
- Machine learning should include testing and refinement.
In conclusion, AI is not going away anytime soon, as technology continues to advance the risks associated with AI will also continue to evolve. We all (organizations inclusive) have a responsibility to learn more and better equip ourselves against potential artificial intelligence risks and control those risks.
