Last Updated on September 27, 2024 by Nadeem Ahmed
Only a few years back, AI was an emerging technology surrounded by much curiosity and anticipation. Today, it turns out to be one of the most widely adopted technologies whose disruption the world can no longer ignore. AI has far wider applications across industries and many emerging innovations are anchored to it compared to other technologies. A study by IDC projects that annual spending on AI by 2024 will reach $ 110 billion. The demand for AI skills is high and rising and the skills gap getting wider by the day. Professionals are constantly on a quest to build their skills through continuous learning and courses like the Post Graduate Program in AI and Machine Learning are becoming as basic as introductory courses as more advanced specialized AI courses come up.
Artificial intelligence (AI) is rapidly becoming an integral part of our lives, from voice assistants and self-driving cars to facial recognition systems and medical diagnoses. However, as AI technologies continue to advance and become more sophisticated, ethical concerns are also growing. There are several ethical issues surrounding AI that must be addressed in order to ensure that the technology is developed and used in a responsible and ethical manner.
AI’s usefulness has been witnessed in the retail, banking, healthcare, and other sectors for conducting research, detecting fraud, making marketing forecasts, and performing predictions among other numerous other applications. AI intelligent machines promise to deliver greater efficiency at a lower cost and make human lives more comfortable. Yet the complexity and broadness of the AI discipline pose challenges, yet to be unearthed, that if not checked, will make it a more harmful than useful invention.
Is it time to slow down a bit to consider the challenges that AI, in all its ubiquity, poses to society?
Indeed the time is ripe to consider the challenges arising from AI technologies and find ways of tackling them early enough.
Table of Contents
Ethical issues in artificial intelligence
Conversations are already happening about the impact of AI on society and its people. We discuss some common issues born out of these conversations.
Oversight, regulation, and control
The reason why AI has drawn so much interest across the board is that it mimics human intelligence. There have been great strides in the development and use of AI-powered applications and AI is fast maturing as a technology a decade later. However, while everyone agrees that regulation and control of some sort should be in place, this is as far as it goes. There is a lack of lacks consensus on how AI should be regulated and it becomes more complex owing to the fact that AI is a fast-evolving technology whose applications are wide-spanning most if not all industries including healthcare, banking, and finance sectors which are considered sensitive in nature.
- Who should regulate AI?
- Who is responsible for coming up with the rules and regulations that govern AI?
Thus, developers, users, and beneficiaries of AI rely on existing laws, developers’ policies, and forces that shape the AI discipline with no neutral oversight authority to regulate the biases, discrimination, and vested interests associated with AI.
Data Privacy
In this era of digital migration and big data, data privacy is a big concern. There is more data today than has ever been accumulated in history. AI relies on data to train its models. The greatest concern today is how safe is personal data? How can we be sure that users of data obtain consent and comply with the regulations in place before and when using data?
Data is a highly demanded and widely traded commodity. Is there more that needs to be done than what is in place to regulate and legislate the collection, distribution, and use of data? How well is personal information protected by the relevant authorities?
Biases and discrimination
There is a high possibility backed by evidence of AI delivering bias and discrimination. A good example is a simple search on Google or other AI-powered search engines that deliver biased results, for instance, of decently dressed men versus skimpily dressed women, or superior whites versus inferior blacks, and the list goes on. These biases stem from algorithms that prioritize popular searches based on those with the most clicks, visits, or highest traffic. This also applies to resume-screening software and digital lending software.
These biases typically often exist in the data used to develop and train AI models as such replicating the biases, stereotypes, and discriminations that exist in our society today. This is to means that AI can be used as a channel to either uphold or minimize the biases we see in the world today. The greatest challenge, therefore, is to ensure that while AI models deliver accurate results, for instance, accurate representation of women, these results are also neutral and unbiased thus not replicating failure in our systems. Also, a mechanism that deals with such biases should be in place. AI will be of greater value when it makes our lives easier while at the same time helping to overcome social biases.
AI morality and the place of human judgment
Our point NO. 3 is an indication that bias can stem from human judgment and be replicated on AI models. On the other hand, as we strive for a neutral and morally upright society, human judgment cannot completely be delegated to intelligent machines. We are not losing ourselves to decisions made by machines. There is an element of human judgment that cannot entirely be replaced by machines and that is morality.
For instance, an autonomous vehicle is in no position to make a moral split-second decision in an emergency traffic situation. For instance, it may not instantly slam on the brakes if a child unexpectedly runs across the road. It may take longer and more intense training for models to sense and instantly act in emergency situations.
Security
Concerns about data privacy are directly connected to the security of data. Cybersecurity presents a huge challenge in a world where data rules. With each passing day, data, ts systems, and processes are exposed to more sophisticated threats. In addition, AI systems are exposed to such threats as model poisoning attacks.
Secondly, such powerful technologies with widespread applications are often the target for being used for criminal and other malicious activities.
AI impact on the environment
Technology has not only impacted human lives and societal values but it also to a certain extent, has an impact on the environment, AI included. AI is known to streamline processes to improve performance and productivity at lower costs. Ultimately, energy consumption is lower with the adoption of AI tools and systems. Curiously, however, it may have huge energy footprints during the development and deployment of systems as well as during the research and development of newer inventions. This is something that needs looking into.
AI impact on human contact and interaction
Humans are naturally social beings that thrive on social interactions. It would not be wrong to say that some of the greatest inventions of our time have been born out of humans interacting with each other. Regardless of the sector that AI is being adopted in, no amount of technology can replace human contact and interaction. Sadly, this could happen sooner or later if AI bots are deployed to take on some critical roles previously done by humans.
Consider bots handling humans in the care sector. The touch of humanity, which includes care, empathy, and relationships, may be lost somewhere along the way. Humans need human interaction to thrive. For this reason, it is important to consider how AI tools and systems can work alongside and not replace humans completely.
AI was most certainly invented for the good of humanity, to make lives better, easier, and more comfortable. AI has taken over the dull, repetitive tasks that humans did and is now performing them fast, productively, and without errors saving companies a great deal of loss.
On the other hand, however, the world, AI inventors, experts, and other stakeholders should not shut their eyes to the ethical challenges posed by this noble technology. It is good, yet it must be regulated to deliver the utmost benefits and be less harmful to humans.
Basic Facts To Know
One major ethical issue in AI is the potential for bias and discrimination. Machine learning algorithms are only as unbiased as the data they are trained on, which means that if the data contains biased or discriminatory information, the AI system will perpetuate that bias. This can have serious consequences, particularly in areas such as hiring and lending, where biases can result in discrimination against certain groups of people.
Another ethical issue in AI is transparency and explainability. As AI systems become more complex, it can be difficult to understand how they make decisions. This lack of transparency can make it difficult to hold AI systems accountable for their actions, particularly in cases where the system makes a mistake or causes harm.
Finally, there is the issue of privacy and data security. AI systems rely on vast amounts of data to function, and this data often contains sensitive information about individuals. It is important that AI developers and users take steps to protect this data and ensure that it is only used for its intended purpose. It is advantageous to educate oneself on AI and enroll in a quality course on the subject. Discover the most popular programming and AI courses and the four key reasons to choose Codora for your programming journey. Benefit from personalized support with small course groups for individual attention, learn from experienced and passionate coaches with practical insights, master theory through hands-on projects, and enjoy collaborative on-site lessons in Zurich to build connections without the challenges of online platforms.
Overall, while AI has the potential to bring many benefits to society, it is important to address these ethical issues in order to ensure that the technology is developed and used in a way that is fair, transparent, and accountable.
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