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The Ethics of AI: Balancing Progress and Responsibility

Karol Przystalski c529978f2b

27/04/2023 |

14 min read

Karol Przystalski

From autonomous vehicles to voice assistants, new technologies have become extremely important in our daily lives. While some hail AI as a revolutionary technology that has the potential to transform our world, others are concerned about its potential dangers.

As AI tools continue advancing at breakneck speed, it's crucial to examine the ethical challenges of their development. How can we balance the progress of AI with the responsibility to ensure that it's safe, transparent, and unbiased? In this article, we'll explore the current state of responsible AI and why it's more important than ever to discuss its applied ethics. Or lack thereof. 

 

Table of contents:

  1. The human brain: we are creatures of habit
  2. The machine’s neural network: your job – automated
  3. Balancing progress and responsibility: why is AI ethics important?
  4. Conclusion: boost your company image with ethical AI

The human brain: we are creatures of habit

Change is not popular; we are creatures of habit as human beings. “I want it to be the way it was.” But if you continue the way it was, there will be no “is.” – Robin Williams, actor 

New always sounds unsettling. At least at the beginning of the novelty introduction, each drawback is typically amplified by human judgment at least 100 times. The invention of the steam engine, the telephone, the internet, and the personal computer are all examples of emerging technologies initially met with skepticism but have since become indispensable in modern life. 

Ideas work similarly, beginning as hopeful wishes and leading to a revolutionary shift in society's mindset. But why are some ideas generally exciting while others are not? 

Historically speaking, lack of knowledge, limited access to the invention, or the target audience’s background (access to higher education, social norms, or beliefs) prevented people from supporting the novelty. Every technological leap made our ancestors question the safety (=stability) of their jobs, whether they should even use the invention or engage in a boycott to prevent the risky concept from becoming widely accepted.

This radical thinking is usually not the case in modern societies, which treat new inventions with acceptance if they provide entertainment or utility, and with considerable caution if they cross the line of utility and potentially substitute our own skills. 

And that is precisely the path Artificial Intelligence has taken in recent years, thanks to several key breakthroughs, such as the development of machine learning algorithms and deep neural networks, which have enabled AI systems to learn and adapt to complex environments. After some time – and the revolution caused by the Chat GPT release, followed by Midjourney, Copilot, and other AI-powered tools – pushed by human dignity, we started to ask questions again.

What’s the AI future? Is my job safe? Can AI become smarter than humans? What are AI ethics? And shouldn’t we just slow down its progression to protect the economy? 

This cautious attitude is unavoidable when we talk about progress – as each breakthrough results in a noticeable change in the lifestyle of the witnessing generation. But for this change to be truly useful, we should evaluate (and address) all concerns related to the invention – so we won't leave any potential loopholes for the future. 

That is why we will now delve deeper into AI ethics, which is critical for providing an ethical framework for machine and human interaction in the digital world.

The machine’s neural network: your job – automated

Every once in a while, a revolutionary product [invention] comes along that changes everything. - Steve Jobs

Artificial intelligence (AI) has come a long way since its inception in the mid-twentieth century. It is becoming increasingly sophisticated and accurate in understanding human language and behavior as machine learning and natural language processing advances. Starting with written text, it progressed to responding to our voice and analyzing images, eventually taking over the assistive role in both doing and reasoning.

The results of that revolution were quickly noticed and commercialized by the private sector. The practical use of AI in business operations increased efficiency, cost savings, improved customer experience, and decision-making. AI is now successfully used to automate repetitive tasks, reducing human error and increasing productivity. For example, by allowing chatbots to handle simple queries, employees can focus on more strategic and value-added work. AI can also assist business leaders in gaining insights from large amounts of data, resulting in more informed decision-making and better outcomes.

Despite the potential benefits of AI, the fundamental problem lies in many ethical concerns, myths, and misconceptions surrounding its adoption. These include the possibility of bias and discrimination, the loss of jobs due to automation, and the possibility of unintended consequences.

Let’s address them one by one. 

1) Will AI take over our jobs?

One common myth is that AI – sometimes imagined as a single-minded collective of physical machines - will ultimately replace human workers, resulting in mass unemployment and the human race's fall [or doom]. As the potential and number of AI technologies grow, more representations of various jobs are raising concerns. Should we be concerned?

Although the change is coming, instead of fearing it, we should embrace it. While AI automates some tasks, it is unlikely to replace the need for human workers. We should view it as an assistant rather than a replacement for qualified workers. People are still required to oversee the processes handled by AI and the quality delivered by automation. With this understanding, AI is more likely to augment human capabilities, allowing us to work more effectively while avoiding the tiredness and frustration associated with task overload. In other words, by collaborating with autonomous systems, humans can monitor and mitigate the potential for bias and discrimination, ensuring the responsible use of AI.

And what about the jobs that may be lost due to a high percentage of soon-to-be-automated tasks? Even as technology advances, it still lacks many human-like traits such as compassion, humor, context understanding, abstract thinking, and overall personality, which are at the heart of many brands' customer policies. In short, AI functionalities are data-driven, so the decisive factor remains on our side.

The path to automation acknowledges the importance of human expertise and experience while leveraging AI's power to improve decision-making and outcomes. At the same time, a human touch is required to provide an exceptional customer-centric experience by an actual employee from flesh and bone, which is, by the way, less tired and more productive due to the unclogging of the repetitive routine.

2) What about the existential Risk of Superintelligence? Can AI become bad? 

This concern became deeply rooted in our culture due to the wide range of sci-fi films, which typically focus on machines becoming aware, which simply translates to becoming bad. The ability to interconnect multiple systems around us to gather real-time data against our will continuously terrifies generations.

As AI advances, it may surpass human intelligence, resulting in unanticipated consequences. Once again, the unknown scares us. However, there are ongoing efforts to ensure that AI is developed ethically and responsibly, with organizations such as the Partnership on AI and the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems working to establish guidelines and standards for AI development. The European Commission, which has collected several AI regulations in its dedicated package, has also expressed a need for AI ethics guidelines.

Ultimately, the future of AI will be determined by how it is developed and used by society, and it will be up to us to steer it in a direction that benefits humanity.

3) Should we trust machine ethics? Is trustworthy AI even a possibility?

Despite its benefits, AI is not without flaws, and biases are a major source of concern. Biases are inherently present in human decision-making based on our experiences, values, and beliefs. Similarly, AI systems are only as good as the data they are trained on. 

One possible source of this problem is human flaws, which creep in when AI researchers feed biased hypotheses to AI code. Another example is low-quality data, which, like stereotypes, focuses on surface information.

As a result, if the data is biased, the results will also be biased. This usually happens when the data used to train an AI system is not diverse or chosen without proper randomization matched to the population it serves (selection bias). Or when – in contrast – certain groups are oversampled in the dataset, but the frequency of events in the training dataset doesn’t accurately reflect reality (reporting bias).

The outcomes are usually unfavorable, resulting in the i.e. development of a healthcare AI system biased against specific demographics. Or a fraud detection system that flags the entire region based on a single reported action. Or, an ineffective surveillance technology used by police and courtrooms that lacks credibility, particularly concerning people of color (which was proven to be showing a worrying 40% of false matches with mugshots in 2018). 

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Potential sources of bias as shown in the healthcare-related example | Source: World Economic Forum

Another source of ethical issues is feedback from users who interact with AI models in the real world. People may unknowingly (or in the name of joy) reinforce bias already built into existing AI applications. For example, a credit card company may use an AI algorithm with a slight social bias to advertise its products to less educated people with higher interest rate offers. Unaware that other social groups are being presented with better offers, these individuals may find themselves clicking on these ads, exacerbating the already existing bias. Joking around with algorithms like Chat GPT also influences AI ethics.

This brings us to another AI-related issue that concerns modern society: confirmation bias, which occurs when AI systems reinforce previously held beliefs or stereotypes. As a result, an AI system used in the hiring process may be biased against candidates who do not fit the typical profile of an employee in that industry (group attribution bias). The Google Translate tool may produce biased results in relation to gender-neutral pronouns based on reports or social media posts (implicit bias). Or, in finance, AI-derived credit scores can perpetuate discriminatory lending practices.

Interestingly, even when protected classes are removed from the training, the model can still produce biased results by relying on related non-protected factors, such as geographic data – a phenomenon known as proxy discrimination.

Overall, AI has the potential to reduce biases in decision-making by removing human subjectivity and introducing objectivity and consistency. By identifying and addressing biases in AI, we can ensure that these systems are used fairly and responsibly, benefiting society as a whole.

And the best way to build trustworthy AI is to promote the responsible use of data sets through industry-wide regulations.

Balancing progress and responsibility: why is AI ethics important?

In today's business landscape, AI is already significantly impacting our lives, with chatbots, predictive analytics, and supply chain optimization being used to help modern humanity. But what role will AI play in future developments?

AI technology is primarily intended to improve human brain intelligence by analyzing massive amounts of data. With the increasing use of AI in sensitive areas such as finance, criminal justice, and healthcare, we must strive to create algorithms that are fair to all. However, as AI systems become more autonomous and sophisticated, questions of accountability and responsibility arise. What happens if an AI system makes a mistake? How can biases in AI design be avoided?

Biased AI can have far-reaching consequences, such as unfair treatment, mistrust, and reputation loss. It can also cause friction when we use it to make decisions that affect society without fully comprehending its decision-making process.

The need for ethical use: responsibilities of AI Creators

As artificial intelligence becomes more integrated into our daily lives, we must consider the ethical implications of its development and use. Ethical AI design and operation are required regardless of the technology used or whether your AI solutions are on-device or in the cloud (or a hybrid of the two).

AI developers must ensure that their solutions are ethically and responsibly designed and implemented, considering the potential impact on individuals, communities, and society. Considerations such as data privacy and security, the possibility of bias and discrimination, and the effect on employment and human rights are all part of this.

By taking a proactive and ethical approach to AI development, we can ensure that these systems are designed and implemented to benefit humanity as a whole while minimizing the potential for harm. Ultimately, the success of AI will be determined by our ability to strike a balance between technological innovation and ethical responsibility, resulting in a future in which AI works for us rather than against us.

Responsible AI: The six ethical principles (by Microsoft)

  • Fairness – all classes of users should be treated fairly; it’s important to note that this rule applies to the system's actual behavior. In other words, the AI developer must ensure that the algorithm is not fed with biased data that could lead to discrimination against specific groups of people. Training sets should be diverse, and the results should be closely monitored after deployment.
  • Reliability & Safety – the algorithm should be able to handle a wide range of scenarios safely. In practice, this means testing it under various conditions, such as a sudden spike in queries, imprecise requests, foreign language input, and database issues. If a system performs well in testing but fails in real-world scenarios, it does not meet the reliability and safety standards demanded by an artificial intelligence solution.
  • Privacy & Security the data set should be stored with appropriate respect and security. If an AI does not require sensitive information such as Social Security numbers, names, phone numbers, E-Mail addresses, or other personally identifiable information. In that case, it is best to keep such information out of anything sent to such an algorithm to reduce the possibility of future violations.
  • Inclusiveness – Artificial intelligence solutions should be available to everyone, regardless of disabilities or impairments.
  • Transparency AI developers must be honest with users about systems' potential limitations, informing them about potential inaccuracies (i.e., false positive/negative results, need for assistance). The rule also emphasizes the importance of understanding how AI tools work and debugging their operations.
  • Accountability – Artificial intelligence solutions must be accountable to local, state, and federal authorities, relevant regulations, and corporate leadership. Ethics in artificial intelligence cannot be an afterthought; rather, it must be a constant consideration throughout AI solutions' design, development, evaluation, and operation.
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Human AI guidelines in relation to the model responsibility | Source: Microsoft Guidelines

Conclusion: boost your company image with ethical AI

Many people are curious about the future of AI and what it may hold for humanity. As AI technology advances, business leaders must consider the ethical implications of incorporating AI into their operations and ensure that AI systems are transparent, accountable, and unbiased.

This necessitates that companies be open and honest with users about how their data is collected and used and obtain their consent before sharing their data with AI. Even with permission, it is critical to ensure that appropriate safeguards (clear policies and guidelines) are in place to protect the privacy and security of that data. And do so morally and responsibly.

Data scientists must actively seek out and address biases in AI systems. Data used to train AI models should be diverse and represent various groups. They must always consider the potential impact on individuals and communities and ensure that AI is not discriminatory or harmful. Businesses can ensure that their use of AI aligns with ethical and responsible data practices by taking these steps, protecting both their customers and their brand reputation.

Keep in mind that the use of AI has a significant impact on brand perception. As a result, accountability for program implementation is critical to achieving the desired outcome. If you're a business owner, consider hiring an ethical AI development firm to help you navigate this exciting and rapidly evolving field.

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Karol Przystalski c529978f2b

Karol Przystalski

CTO at Codete. In 2015, he received his Ph.D. from the Institute of Fundamental Technological Research of the Polish Academy of Sciences. His area of expertise is artificial intelligence.

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