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Top Ethical Challenges in AI – The Price of Progress

Ethical challenges in AI
Published on Mar 24, 2022

In today's digital era, artificial intelligence (AI) and machine learning (ML) are everywhere - from facial recognition to algorithms for pandemic outbreak mitigation and healthcare.  

What AI does is automate the judgments as —yes, no; right, wrong. 

  • But are these technologies, that can mirror human intelligence, built in consensus with human ethics?  
  • Can we create new regulatory norms to practice AI ethically? 
  • How can we use AI to our advantage and mitigate its ill effects? 

Today, AI is becoming ubiquitous, in and out of the workplace. With artificial intelligence (AI) becoming more powerful, the questions that surround AI ethics are becoming more relevant.  

But can technology be controlled to avoid adverse outcomes?  

Fortunately, these concerns are driving action in the public and commercial sectors. Organizations using AI-based applications are launching several initiatives to address these ethical concerns and ensure their responsible use.  

AI is essential across diverse industries, like health care, banking, retail, and manufacturing, but its game-changing promise is giving rise to threats that can cause more societal harm than economic good. AI presents three major ethical concerns for human society-  

  • Privacy and surveillance 
  • Bias and discrimination 
  • Role of human judgment 

The importance of ethics in AI originates from the power of what can be accomplished with AI when combined with machines, including self-driving cars, robots & humans co-working in factories, remote surgeries. Irrespective of the other transformative technologies that came before, AI is prompting a fair amount of skepticism. This fear is giving birth to regulations and policies to curb the scope of its application.  

Read more: Humans & Robots Coworking; Rise in Automation; Is this the Smart Future of Work? 

AI advancing in other domains

Diverse ethical risks in Artificial Intelligence 

The ethical risks associated with AI differ from sector to sector and arise due to a variety of factors like the role played by datasets in AI systems, the applications of AI technology, and the capabilities demonstrated by systems like automatic learning. Listed below are some prominent ethical issues associated with AI system design, development, and deployment:  

  • Lack of transparency 

Consumers and other parties affected by technology will likely want to learn about how the system is affecting their work - what data it is using and how it is making informed decisions. However, AI-developed systems entail building effective models whose inner workings are not well comprehended and cannot be explained—they are known as black boxes.  

While techniques are emerging that are helping to shine a light inside the black box of specific machine learning models, making these systems more interpretable and accurate is not suitable. By practicing ethical AI, businesses can consider being transparent about the functioning of systems and data as a responsibility. 

  • End of privacy 

Large sets of personal data are collected by many companies from consumers when they register with them. This data can be employed to train AI-based systems for targeted advertising and personalized promotions. Ethical issues arise when that data is used for a different purpose, like training the system to make employment offers without the users' consent. A recent study underlined that 60 percent of customers are concerned about AI systems compromising their personal data.  

To build customer trust, companies need to adopt transparent means to collect data and offer a clearer mechanism for user consent to protect their individual privacy. 

AI market to break the revenue rate

  • Poor accountability 

AI is increasingly automating the decision-making process for several critical applications, like autonomous driving, wealth management, and disease diagnosis. 

The concern that arises is around who might bear the responsibility for the harm associated with these AI systems. 

For example, if a self-driving car does not stop at the sight of a pedestrian and hits him/her, who will be held accountable - the car manufacturing company, the passenger, or the owner?  

Existing accountability mechanisms are at a loss while addressing such scenarios. Businesses and governments need to work toward employing ethical accountability structures for AI-based technology. 

  • Automated Decisions  

Al algorithms and training data contain biases as they are generated by humans. These biases prevent AI models from making fair decisions. These biases in AI systems are due to two significant reasons.  

  1. Developers programming biased AI systems without noticing 
  2. Using historical data to train AI algorithms that may not fairly represent the whole population 

Biased AI algorithms can lead to discrimination. Amazon had to close its AI recruiting tool after employing it for one year. 

The reason - Developers stated that the tool was penalizing women. Of the chosen candidates, the AI tool selected about 60% of male candidates for the vacant positions. This was due to the patterns in historical data on Amazon’s recruitments. 

Getting rid of biases in AI systems is important to building an ethical & responsible AI. But achieving this scenario is almost impossible due to existing human biases and the ongoing identification of new biases. 

AI in workplace

  • Lack of Purpose & Meaning leading to Unemployment  

AI is already being perceived as a potential threat to certain job categories. Automation of industry has been a contributing factor in job loss. AI is likely to extend this trend to other fields, including law, medicine, and education.   

Attached to this concern of unemployment is the concern for what the future for humanity looks like. What will millions of unemployed individuals do? How will they contribute to the well-being of society?  

While it is not clear what unemployed people ultimately will be able to transition to, it is important for businesses and governments to employ ethical means to avoid the vile circumstances that lie before humanity. 

 Read more: Top AI Trends to Watch Out for in 2022 

  • Environmental Effects 

Machine learning models demand enormous amounts of energy to train the systems. The cost of this amount of energy can run into tens of millions of dollars or more. The generation of this energy involves the use of fossil fuels, which is negatively impacting the ongoing climate crisis. 

On the contrary, machine learning can make electrical distribution much more efficient and operate to solve biodiversity, environmental research, and resource management problems. AI is a technology that focuses on efficiency. Artificial Intelligence can be a net positive for the environment if employed in the direction of increasing energy efficiency. 

Revenues for the AI market

The Rise in Ethical Concerns due to AI 

AI ethics applies to both the goal of the AI solution and forms a critical part of the AI solution. While elements of AI—machine learning, deep learning, and NLP—were designed to operate ethically, AI is being used to achieve unethical business outcomes. 

Through neural networks, machine learning is advancing rapidly due to the following:  

  1. Huge increase in data banks 

  1. Huge increase in computing power 

  1. Huge improvement in ML algorithms 

With an increasing number of companies considering AI as a critical element of the future, concerns about its possible misuse are also on the rise.  

While early on, it was assumed that the future of AI would involve automation of simple tasks that require low-level decision-making, AI, now, is rapidly growing into more powerful computers that are posing great risks to its innovators. 

But the AI concerns are not limited to controversial applications of technology like automated weapons. The infusion of AI into common activities, including social media interactions, employee hiring processes, and credit decisions, can lead to unintended outcomes.  

We have a long way ahead before artificial intelligence gels well with ethics. But until then, it is imperative on our part to self-police the use of AI and employ ethical practices. 

Read more: Top AI Stocks to Watch Out for in 2022 

Conclusion

New technologies always bring benefits and risks, and AI is no exception. These technologies are improving and disrupting human lives at the same time. While new technologies are created to achieve something good, AI offers amazing new abilities to help make the world a better place. 

Artificial intelligence is rapidly transforming the digital landscape and will continue to do so. This transformation is likely to have deep ethical impacts. AI offers, in an amplified form, everything that humanity already is, both good as well as evil. And with the emergence of AI, much is at stake.  

AI has gotten so powerful and efficient that it can leave humans feeling inferior. While businesses are taking advantage of AI to improve their strategies and performance, they should also consider the ethical questions arising due to the technology and work towards developing their capacity to leverage it in an ethically responsible way.  

With AI automating more of our jobs, it is not only replicating human biases but also conferring a sense of credibility on these biases.  

What will be our contribution as human beings? Will artificial intelligence continue to replace all our jobs? 

Through the collaborative effort of individuals and organizations, let's hope that AI will help us to make a better world. 

With offices in New York, San Francisco, Austin, Seattle, Toronto, London, Zurich, Pune, and Hyderabad, SG Analytics, a pioneer in Research and Analytics, offers tailor-made services to enterprises worldwide. A leader in RPA Consulting, SG Analytics helps companies embrace workforce transformation through digital assistants. Contact us today if you are looking to make critical data-driven decisions that facilitate accelerated growth and breakthrough performance. 


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