Top 7 Ethical Issues In Artificial Intelligence

Artificial intelligence and machine learning technologies are rapidly reshaping society and will do so for the foreseeable future. With these powerful new technologies both benefiting and harming human lives, this social transformation will have a profound ethical influence. AI, being the externalization of human intelligence, magnifies everything that mankind already is, both good and terrible. There is a lot at stake. We should think very carefully about how to make this shift at this point in history, or we risk encouraging the darker part of our nature rather than the lighter.

 

Why is AI ethics becoming a concern right now? Machine learning (ML) via neural networks is fast advancing for three reasons:

 

• Significant growth in data set size; 
• Significant increase in computer power; 
• A significant development in ML algorithms and more human skills to write them. All 

 

Three of these developments involve the concentration of power, and "great power comes great responsibility."

 

Brief about Artificial Intelligence?

 

Artificial intelligence (AI) is a broad field of computer science concerned with creating intelligent machines capable of doing activities that normally require human intelligence. While AI is an interdisciplinary discipline with many techniques, advances in machine learning and deep learning in particular are causing a paradigm shift in almost every sector of the IT industry.

 

Artificial intelligence enables machines to mimic or even surpass the capabilities of the human mind. From self-driving cars to the growth of smart assistants like Siri and Alexa, AI is fast becoming a part of everyday life — and an area in which corporations across all industries are investing. The ability of artificial intelligence to rationalize and execute actions that have the best likelihood of reaching a certain goal is its ideal feature. 

 

Machine learning (ML) is a subset of artificial intelligence that refers to the concept that computer programs can automatically learn from and adapt to new data without the assistance of humans. Deep learning approaches facilitate autonomous learning by absorbing massive volumes of unstructured data such as text, photos, or video.

 

In general, artificially intelligent systems can execute tasks generally associated with human cognitive functions, such as voice interpretation, gameplay, and pattern recognition. They often learn how to do so by sifting through enormous volumes of data in search of patterns to model in their own decision-making. Humans will often supervise an AI's learning process, praising positive decisions while discouraging bad ones. However, some AI systems are designed to learn without supervision, such as by repeatedly playing a video game until they figure out the rules and how to win.

 

Also Read | Edge AI: A Step Towards Next-Gen AI Applications

 

Ethical Issues with Artificial Intelligence? 

 

Intelligent machine systems are changing our lives for the better every day. Our world will become more efficient as these systems become more capable. Some of today's technology titans believe that artificial intelligence (AI) should be used more widely. However, many ethical and risk assessment issues must be addressed before this can become a reality. These are discussed further below:

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Top Ethical Issues With AI

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1. Technical Security:

 

The first thing to ask about any technology is if it functions as it should. Will AI systems deliver on their promises, or will they fail? What will be the consequences of such failures if and when they occur? And, if we rely on them, will we be able to survive without them? 

 

Several people have perished in semi-autonomous car accidents, for example, when the cars encountered situations in which they failed to make safe decisions. While writing very detailed contracts that limit liability may reduce a manufacturer's legal responsibility, from a moral standpoint, not only is responsibility still with the company, but the contract itself can be viewed as an unethical scheme to avoid legitimate responsibility.

 

The issue of technical safety and failure is distinct from the issue of whether a well-operating technology can be employed for good or evil (issues 3 and 4, below). This is only a function question, but it is the foundation upon which the remainder of the analysis must be built.

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2. Inequality: 

 

Our economic system is founded on remuneration for contributions to the economy, which is frequently measured using hourly pay. When it comes to products and services, the bulk of businesses still rely on hourly labor. However, by utilizing artificial intelligence, a company can drastically reduce its reliance on the human workforce, resulting in fewer people receiving revenue. As a result, those with ownership in AI-driven enterprises will make all of the money.

 

We are already witnessing an increasing wealth disparity, with start-up founders reaping a disproportionate share of the economic surplus they generate. In 2014, the three largest companies in Detroit and the three largest corporations in Silicon Valley made nearly the same revenues but in Silicon Valley, there were ten times fewer employees.

 

3. Potentially Harmful Mistakes:

 

Learning produces intelligence, whether you're a human or a machine. Systems typically go through a training phase in which they "learn" to recognize the correct patterns and behave in response to their input. Following the training phase, the system moves on to the testing phase, where additional scenarios are thrown at it to see how it performs.

 

Since it is highly unlikely that the training phase will cover all of the possible scenarios that the system will face in the real world, the system can be fooled in ways that humans would not be. As a result, if we are to rely on AI to replace human labor, we must ensure that it works as intended and cannot be dominated by people with selfish motives.

 

4. Transparency and confidentiality:

 

Can we actually understand how the technology works and collect data on its operation once we've determined that it works properly? Ethical analysis always begins with gathering information; only then can evaluation begin.

 

It turns out that some machine learning techniques, such as deep learning in neural networks, make it difficult or impossible to truly grasp why the system makes the choices it does. In other circumstances, the machine may be able to explain something, but the explanation is too complex for humans to comprehend.

 

5. Humanity: 

 

AI bots are becoming increasingly adept at simulating human interaction and relationships. Eugene Goostman, a bot, won the Turing Challenge for the first time in 2015. Human raters used text input to interact with an unknown entity in this task, then judged whether they were chatting with a human or a machine. Eugene Goostman duped more than half of the human raters into thinking they were speaking with a human.

 

This is just the beginning of an era in which we will routinely deal with machines as if they were humans, whether in customer service or sales. While humans are limited in the amount of time and attention they can devote to another person, artificial bots can devote virtually unlimited resources to developing relationships.

 

6. Beneficial Application and Capacity for Good:

 

The primary goal of AI, like any other technology, is to help humans live longer, more prosperous, and more rewarding lives. This is good, and as long as AI assists people in these ways, we may be grateful and embrace the benefits it provides.

 

Archaeology, biomedical research, communication, data analytics, education, energy efficiency, environmental protection, farming, finance, legal services, medical diagnostics, resource management, space exploration, transportation, waste management, and other fields are likely to benefit from increased intelligence.

 

7. Robots that are not racist:

 

Though artificial intelligence has far greater processing speed and capacity than 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 uses AI to identify people, objects, and scenes. However, it can go awry, as when a camera's racial sensitivity was off, or when software used to forecast future offenders exhibited a bias towards black people.

 

We must remember that AI systems are designed by humans, who can be biased and judgmental. Once again, if used correctly or by those who seek social progress, artificial intelligence can serve as a catalyst for positive change.

 

Also Read | Role of Artificial Intelligence in Storage Management

 

Benefits offered by AI

 

The existence of AI is transforming our society, and more career opportunities—from data scientists to information managers to software developers—are becoming available on a daily basis. Here are ways in which how artificial intelligence is influencing and improving our lives:

 

1. Making Sound Decisions:

 

AI technology is being used by businesses to optimize their daily procedures, study upcoming trends, anticipate growth, and predict results. For example, when a client adds an item to their shopping basket on the websites of some big retailers, they are immediately offered an extra suggested item to buy based on an advanced algorithm. This algorithm was designed to compare thousands of other customers who purchased similar items and make an informed recommendation. 

 

2. Aids in the resolution of complex problems:

 

All of the emphasis corporations have placed on the development of AI, as well as all of the expenditures made in the technology, has resulted in major improvements. Machine and deep learning models are now assisting AI in solving some hard problems. Some business sectors, for example, are now using artificial intelligence to detect fraud and create personalized interactions with customers. In many circumstances, clients can handle their difficulties without ever speaking with a human!

 

3. Increased Customer Satisfaction:

 

The days of dialing a number and waiting on hold to talk with a representative are soon becoming a thing of the past. Many businesses now use online chatbots to make responding to and resolving customer concerns easier. Chatbots may learn and mimic natural human discourse using programmed natural language processing (NLP). Chatbots also employ prediction algorithms to learn and react to each customer's query, resulting in quick and customer-centered responses.

 

4. Data Analysis and Research:

 

AI enables researchers and data scientists to better understand trends, forecast results, and make modifications in half the time. What would have taken months to gather may now be done in minutes, if not seconds. For example, a language learning software, such as Duolingo or Babbel, may notice that half of its users reach a plateau in fluency after three months of learning and integrate extra helpful courses to close the gap.  

 

Alternatively, a meal delivery business may utilize an algorithm to discover that stay-at-home moms check their emails and meal plan more frequently in the mornings, and then pivot their email marketing to achieve the greatest outcomes.

 

Conclusion

 

When we accept machines as entities capable of perception, emotion, and action, it's not a big leap to examine their legal position. Should they be handled as if they were intelligent animals? Will we think about the pain of "feeling" machines?

 

Some ethical problems are about reducing suffering, while others are about risking unpleasant results. While we consider these risks, we should also remember that technological progress, on the whole, means better lives for everyone. Artificial intelligence has enormous promise, and it is up to us to responsibly implement it.