Artificial Intelligence: Underlining The 7 Most Common Ethical Issues

Ever since the world has stepped forward towards the age of digitalization, things have never been the same. From the introduction of the internet to the expansion of the mobile-first concept and innovations like artificial intelligence and machine learning, people have experienced the highest exposure to technology ever.

Amidst all this development and expansion, one thing that has scaled dynamically is Artificial Intelligence. From the expansion of neural networks to energy use, data sets, and the prevalence of society, the growth of AI has made way for significant ethical concerns.

Before we jump on unraveling the most common ethical issues surrounding artificial intelligence, let us begin with developing an understanding of what ethical AI is.

What is ethical AI?

When it comes to “Ethics in AI”, the term means to investigate and constantly question the technologies that can hamper human life. Be it replacing humans with smart machines or concerns related to sharing personal information on AI-powered systems, the concept of ethical AI has gained all the pace due to the rapid scaling of AI technologies.

From computing power to data fed, AI systems have grown tremendously big in the past few years. Moreover, the rapid growth of AI has even dwarfed the potential of computing that was carried back from the era of the internet and PCs.

The extensive scale of deployment and responsibilities given to AI has now even involved other aspects of technology in the picture. Be it deep learning or scaling of any other advanced technologies that involve the use of AI, the situation has escaped the comprehension capabilities of even the most proficient practitioners.

And therefore, ethical AI brings some really interesting and important factors to the light that need immediate consideration in order to overcome ethical concerns surrounding AI technology:

1. Biases

From the training artificial intelligence algorithms to removing the bias involved, a huge amount of data is needed. Consider an example of any application made to allow editing of pictures. These applications are made to use AI to beautify the pictures and therefore contain a vast amount of data that has more white faces over non-white faces.

Therefore, it is necessary that AI algorithms must be trained to recognize and process non-white faces as efficiently as it does for white faces. The process requires feeding the right balance of faces to the database in order to ensure the algorithm works well to cut the built-in bias for beauty apps.

In other words, eliminating bias is extremely necessary when we need to create technology that can reflect our society with greater precision. Such actions thus require identifying all the potential areas of bias and fixing the AI solutions with the right approach.

2. Infusing Morality, Loss of Control

With more and more use of artificial intelligence, machines are capable of making important decisions. Be it the use of drones for delivery by carrier services or building autonomous rockets/missiles that can potentially kill a banned object. However, there is still a need for human involvement in such decision-making that can work on any rules and regulations that can impact humanity in any form.

The concern here is actually allowing AI to work on quick decisions. However, in operations like financial trading where it is essential to make split-second decisions, giving control to humans leaves no chance to make the right move at the right time.

Another example of the same is autonomous cars as they are made to make immediate reactions to take control of situations. The problem with all these scenarios is the ethical challenge of establishing a balance between control and AI.

3. Privacy

One of the most significant ethical concerns that have been long associated with AI is Privacy. There are many ethical concerns, from training AIs to the use of data and its source. Oftentimes, it is assumed that the data is coming from adults with high mental capabilities making the data used for creating AI that can work on choices. However, the situation is not always the same.

A quick example of the same can be the use of AI-powered toys that are designed to converse with children. Here the ethical concerns are about the algorithms collecting data from those conversations and making way for queries like where and how this data is being used.

The ethical concerns with such conversations grow even bigger when it comes to companies collecting that data and selling it to other companies. There is a need for rules that can justify data collection.

Moreover, there must be strict legislation made to protect the user’s privacy as an object that can collect data from conversations with children could potentially be used for taping the conversations of adults within the same environment.

4. Power Balance

The next significant ethical issue that comes with AI is giants like Amazon and Google using technology to dominate their competitors. More importantly, there are countries like China and Russia competing in the AI landscape, and here the question arises of the power balance.

From equal wealth generation to balancing monopolies, it is very likely that countries that are ahead of AI development and implementation are likely to race ahead of others.

For instance, countries with better access to resources that can develop and implement AI could utilize its power to innovate their war strategies, finance building, and more. Thus, AI creates some serious gaps around the subject of power balance.

5. Ownership

At number five, we have another big ethical challenge that needs to identify people or organizations that can be held accountable for things that AI creates. As Artificial Intelligence has all the potential to develop texts, bots, and video content, it is likely to create things that are misleading. Such material could trigger any violent circumstances for a particular community, ethnicity, or belief and therefore it becomes necessary to understand who could take ownership of the content.

Another example of the same could be AIs that are used to create music pieces or art. Thus, it is necessary that any new piece of content developed with AI that reaches some audience must have some ownership or could have intellectual property rights.

6. Environmental Concerns

Most of the time, the companies working on AI are not so concerned about how AI could impact the environment. Developers working on AI assume that they are using data on the cloud to work on their algorithm and then the data works on, say creating suggestions, recommendations, or making automated decisions. Though the systems are running efficiently and effectively, the computers that are keeping up the AI and cloud infrastructure require immense power.

A quick example of the impact that AI could create on the environment is the fact that training in AI could create 17 times more carbon emissions than an average American does in a year. Therefore, it is important that developers find ways to use this energy for other productive purposes and get over one of the most pressing problems of declining energy resources.

7. Humanity

Last but not least, it is the challenge of how humans feel in the presence of AI. Especially, when AI has been developed to be so powerful and efficient, it triggers the challenge for humans missing the feeling of how it actually feels to be human. As AI is designed and created to work on precision, it diminishes the human morale built through making errors and learning from it.

Especially, when AI has automated jobs for so long, it often leads to the question that what contributions human beings could make to the technology landscape. Though it is not possible for AI to replace humans for all jobs, only the idea of augmenting AI possesses some serious challenges.

To conclude

Humans need to get better when working along with smart machines in order to align with the tech transition. Besides, it is extremely necessary for the people to sustain their dignity and have respect for technology. Therefore, it is necessary that all the ethical challenges surrounding AI must be understood.

Especially, when AI is seen as a technology that has all the capability to create user-oriented and sustainable IT solutions, creating ethical AI could help empower digitalization. Be it advancing the process through AI improved Quality Assurance and software testing or using AI itself to create unbiased technology for users across the world.

More importantly, it is crucial that engineers working on AI technology should always have consideration for the human aspect of using AI. Be it the use of AI machines or software, it is vital that transparency should be maintained with respect to user data consumption and human involvement in decision making, the privacy of data, no biases, and the power balance.

Even if the thought of AI systems surpassing human intelligence may appear scary, the key is to have an early vision of all the ethical issues surrounding AI adoption. It not only needs humans to keep on learning but stay informed of the impact that any potential implementations related to AI could have on society.