Artificial intelligence (AI) has become an integral part of our everyday life, business, medicine, and more. The objective of AI is to improve our lives by augmenting human intelligence. Today, Google’s search engines, Facebook’s target advertising, and smart devices including Siri and Alexa are all powered by artificial intelligence. In addition, AI is also the driving force behind self-driving cars, autonomous weapons, predictive policing, and other innovations that could harm human lives without human intervention.
This is why ethics in artificial intelligence has become a topic of debate for many worldwide as AI applications come with their fair share of ethical issues that need to be addressed at the earliest. More recently, Google suspended an engineer who claimed that the AI bot had become more sentient. Such developments question the integrity of the code of AI ethics that these companies follow and whether they pose a threat to human lives in the future.
In this article, we will explore the meaning of AI ethics and understand why AI bias is making more and more people anxious worldwide.
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What is AI ethics?
In simple words, AI ethics is a system of techniques and moral principles that are aimed to ensure the responsible development of AI systems.
Humans have invested a great amount of time to understand how they can leverage big data to their advantage. Besides, the fast-paced advancements in cloud computing coupled with the lightning-fast development of advanced machine learning algorithms have paved the way for a new digitally interconnected world. This interconnected world is providing fertile grounds for AI to make human lives better and make our society a better place.
Innovations in AI have significantly enhanced the provision of critical social goods and services right from transportation, healthcare, food supply, and environmental management. The good news is that these benefits of AI or AI-powered systems are just the tip of the iceberg.
Since machine learning algorithms have the ability to organically improve with increased access to data, these systems will only get better and become more useful in the information age. Many predict that AI technologies will soon become the guardians of sustainable human development and essential public interests.
While the prospects of AI are promising, there are some legitimate concerns linked to the technology. As expected in any emerging and rapidly evolving technology, there is a steep learning curve, which leads to miscalculations and mistakes which could have a negative impact on society. Artificial intelligence is no different and there is a lot of work that needs to be done to ensure that a strong code of AI ethics is adhered to.
Let’s take a look at some of the most common AI ethics questions that are often hurled toward leaders in this domain.
1. Is AI inherently unbiased and ethical?
Although it may appear that AI is neutral, that is not true. AI is only as fair or unbiased as the humans that design it or the data that is fed into the system. Siobhan Hanna, Managing Director of Telus Internationals says that machine learning that compliments AI technologies and automation is a bot built by neutral parties, but human beings with some bias. He further states that we may never manage to get rid of the bias. However, what we can do is restrict the impact of human bias on AI-powered systems.
2. Is AI ethics something to worry about?
Today, C-suite leaders are becoming increasingly aware of the risks involved with biased AI. On the other hand, even employees are becoming anxious due to the negative impact of intelligent automation on jobs.
It is very obvious that companies worldwide are investing in AI to streamline their processes and become more efficient. Having said that, this makes it imperative to have a common set of principles, frameworks, and practices so that all the relevant stakeholders can manage the potential risks of AI and manage their customers and business better.
3. Does cultural diversity impact ethical AI?
One of the most effective ways to identify and eliminate intentional or unintentional biases in AI is to have a culturally diverse team. Diversity enables your brand to be in a better position to behave and think a bit differently when it comes to ethics, safety, trust, and knowledge transfer into AI systems. This will also ensure that the algorithms programmed by human beings with inherent biases are reviewed in the right manner at the very beginning of the development phase.
4. How are top companies addressing the risks of ethical AI?
Ethics in artificial intelligence is important and the top companies are aware of that. They also understand the importance of avoiding data-induced AI bias. This is exactly why CompTIA advocates that there should be balanced label representation in training data. In addition, the goals and objectives of AI models are transparent and clear so that legitimate datasets can be built to test the models for biases.
Some open-source tool kits from companies such as Aequitas can help you evaluate the bias in uploaded data sets. Similarly, Themis-ml and IBM’s AI Fairness 360 offer tools that mitigate bias and have the ability to detect compromised algorithms.
What is even more encouraging to see is that many companies are now creating concrete ethical guidelines for AI development. In addition, these companies are also educating their users about the use of data in AI applications.
By now, companies have realized the importance of ethics in artificial intelligence. This is why, IT leaders, data scientists, and stakeholders alike are coming together to spread more awareness pertaining to AI ethics. Since trust is a major driving factor in the digital era, enterprise IT leaders also need to be educated on the importance of ethical AI and what it means.
It is encouraging to see that while industry standards are gradually maturing, there is a global acceptance that the foundation of development and product architecture should be based on ethics.
What are your thoughts on this subject? Do you think AI systems are biased? Leave your comments below and tell us what you think.
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