Ethical challenges of artificial intelligence

Artificial Intelligence

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13 Mar 2022
8 Min read

Top Challenges Faced By Artificial Intelligence Algorithms

Intelligent machine systems improve our lives by optimizing logistics, detecting fraud, composing art, performing research, and offering translations. Our world grows more efficient and prosperous as these systems become more capable.

Alphabet, Amazon, Facebook, IBM, and Microsoft, as well as top personalities like Stephen Hawking and Elon Musk, believe that now is the ideal time to discuss artificial intelligence’s nearly limitless landscape. This is a new frontier for ethics and risk assessment for growing technologies in many aspects. So, what are the topics and debates that keep artificial intelligence algorithms professionals awake at night?

Unemployment: What Happens When A Job Comes To An End?

The primary concern in the labor hierarchy is automation. As we explore ways to automate tasks, we may allow humans to take on increasingly complex duties, moving away from the physical labor that dominated the pre-industrial era and toward the cognitive labor that typified strategic and administrative work in our globalized society.

On the other hand, self-driving trucks appear to be an ethical decision when considering the lower probability of accidents. Consider the trucking industry, which employs millions of people in the United States alone. What will happen to them if Tesla’s Elon Musk self-driving trucks generally become available in the next decade? The majority of office workers and the bulk of the workforce in wealthy countries could face the same scenario.

We’ve arrived at the point where we must decide how to spend our time. The bulk of people continues to sell their time to provide for themselves and their families. We can only hope that people will be able to find purpose in non-labor activities such as caring for their families, participating in community activities, and discovering new opportunities to support human civilization due to this alternative.

If we make it through the transition successfully, we may one day look back and think it was barbarous that humans were forced to sell the majority of their waking time to survive.

Inequality: What Is The Best Way To Disperse The Money Generated By Machines?

Our economic system is founded on wages for a financial contribution, frequently measured in terms of hourly pay. When it comes to products and services, most businesses still rely on hourly labor. Artificial intelligence, however, enables a company to reduce its reliance on human labor, which results in fewer people earning revenue. As a result, those who control AI-driven firms will be the only ones who get the profit.

We’re already seeing a widening wealth disparity, with start-up founders taking home a disproportionately high share of the economic surplus they generate. For instance, the three most significant companies in Detroit and the three most prominent corporations in Silicon Valley made nearly the same revenues in 2014… but in Silicon Valley, there were ten times fewer employees.

Humanity: In What Ways Do Machines Affect Human Interactions And Behavior?

Artificially intelligent bots are getting better at simulating human communication and relationships. In 2015, Eugene Goostman, a bot, became the first person to win the Turing Challenge. Human raters utilized text input to interact with an unknown entity in this task and then identified whether they were chatting with a human or a machine. Human raters were deceived more than half of the time by Eugene Goostman, who had them think they had been conversing with another person.

This milestone is merely the beginning of an era in which we will interact with machines as if they were humans regularly, whether in customer service or sales. On the other hand, Artificial bots may channel nearly endless resources into forming connections. In contrast, people are restricted in the amount of attention and kindness they can devote to another person.

We are already witnessing how technology may trigger the reward centers in the human brain, even if few of us are aware of it. Take a look at clickbait headlines and video games, for example. A/B testing, a crude algorithmic optimization for content, is frequently used to improve headlines to attract our attention. Many video and mobile games employ this and other techniques to make them addicting. The future frontier of human dependency is technology addiction.

On the other hand, perhaps we can develop a new application for software that has previously proven to be effective at directing human attention and initiating specific behaviors. If employed correctly, this could become a chance to influence society toward more desirable behavior. Nevertheless, in the wrong hands, it might be dangerous.

Artificial Insanity: What Can We Do To Avoid Making Mistakes?

Learning is the source of intelligence, whether you’re a human or a machine. In most cases, systems go through a training phase in which they “learn” to recognize the correct patterns and act on them. A fully trained plan can move to the testing phase, which is subjected to more instances and evaluated.

The training phase will not cover all of the scenarios that a system may encounter in the real world. These systems are susceptible to deception in ways that people are not. Random dot patterns, for example, can cause a plan to “see” things that aren’t there. If we rely on AI to usher us into a new era of work, security, and efficiency, we must ensure that the machine works as intended and that humans cannot manipulate it for their gain.

Robots Rights: How Can We Get Rid Of AI Bias?

Even though artificial intelligence algorithms has processing speeds and capacities far exceeding humans’, it cannot always be trusted to be fair and neutral. Google and its parent firm Alphabet are among the leaders in artificial intelligence, as evidenced by Google Photos, which employs AI to recognize people, objects, and scenes. In some cases, however, it doesn’t work properly, for example when a camera is not sensitive to color or when a software program is biased towards black people.

Conclusion

It’s important to remember that AI systems are designed by people prone to bias and judgment. Artificial intelligence algorithms can, once again, become a catalyst for positive change if employed correctly or by people who aspire for social betterment.

When we view machines as entities capable of perceiving, feeling, and acting, it’s not a giant leap to contemplate their legal position. Should they be handled as if they were intelligent animals? Will we take into account the pain of “feeling” machines?

Some ethical challenges of artificial intelligence are about reducing suffering, while others risk undesirable consequences. While we contemplate these dangers, we must also remember that, in general, technological advancement brings a better life for everyone. Artificial intelligence algorithms has enormous promise, and it is up to us to put it into practice responsibly.

Do you want to know more about artificial intelligence algorithms? To learncontact ONPASSIVE team.

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