This article is authored by Rakesh Prasad, senior vice president, strategy and solutions, Innover.
While Artificial Intelligence (AI) has the potential to revolutionise businesses and improve overall strategy, it also raises important ethical concerns. As AI continues to assimilate, the associated risks of discrimination and opaque decision-making must be carefully considered. A recent survey reports that over 50% of business executives have agreed upon the importance of ensuring that AI systems are ethical and 41% of senior executives report to have abandoned an AI system due to ethical concerns. To build ethical AI, businesses need to consider how its deployment will affect the society, including transparency, accountability, and the protection of individual privacy rights.
A study by Deloitte found that only 21% of businesses believe that their organisation is ready to address the ethical risks posed by AI, highlighting the need for businesses to take a proactive approach to ethical AI development and deployment. The intricacies of AI technology bring about equally complex challenges. AI technology has limitations in understanding complex situations and identifying subtle nuances, which can lead to biased and inaccurate outcomes in decision-making processes. This can have significant implications, particularly in industries where AI-generated predictions play a pivotal role in shaping individuals’ lives, potentially resulting in unfavourable outcomes.
Artificial intelligence systems are only as true as the data they are trained on, and unfortunately, this data is often inherently biased. Data bias can amplify societal biases and discrimination, particularly regarding race, gender, and socioeconomic status, thereby compromising the integrity of the data used for business decision-making. This can occur when the data used to train an AI model is unrepresentative of the population it is intended to serve, or when the data contains implicit biases and stereotypes that are reflected in the model’s predictions.
With businesses increasingly relying on data-driven decision-making, the risk of algorithmic bias also becomes more pronounced. As biased data is used to train systems and computer models, or the design of the algorithm is biased, or there is a lack of diversity among the people who develop and test the algorithm, the resulting output can be skewed and lead to inaccuracies and discrimination. For instance, a leading tech company faced scrutiny over its AI-powered recruitment tool, designed to automate the recruitment process by analysing resumes and ranking candidates. The tool was found to be biased against female candidates as it had learned from the male-dominated resumes in its training data. This led to the tool consistently downgrading resumes containing women’s names or references to women’s colleges. Hence, to ensure accountability, businesses must understand the sources of bias in data and algorithmic interpretation while utilising appropriate tools and techniques to mitigate them for ethical AI development.
An important ethical issue in the field of artificial intelligence is the challenge of establishing accountability. As AI systems become more advanced and independent, it becomes increasingly difficult to determine who is responsible for their actions, especially with opaque decision-making, increasing the responsibility for causing harm. For example, many companies use AI-powered chatbots to handle customer inquiries and support. If a customer has a negative interaction with a chatbot, or if they receive inaccurate information, it can be complicated to identify who is responsible for the error. Should the blame lie with the chatbot developer, the company that deployed it, or the customer service representative who employed it? A survey reveals a mounting need for transparency and accountability in AI systems, with 81% of consumers demanding transparency and 74% expecting accountability for AI decisions. To meet these expectations, businesses must prioritise the development of ethical and transparent AI systems.
Ensuring responsible and ethical use of AI requires both human oversight and regulatory frameworks. Although AI can improve efficiency and automate tasks, it is not error-free or without bias, and human intervention is crucial to ensure the outcomes are reliable and impartial. This also encompasses protecting privacy, security, and intellectual property while balancing ethical considerations with the need for innovation. To achieve a comprehensive framework for responsible AI, it is imperative to consider all aspects of AI’s impact on society and collaborate with various stakeholders to establish guidelines and regulations that promote accountability and ethical practises.
The National Strategy for AI recognises the need for effective policies, standards, and awareness-raising initiatives among key stakeholders to mitigate AI-related risks. Moreover, to avoid AI systems reinforcing social inequalities, businesses and developers must alleviate data and algorithmic biases. This involves selecting and preprocessing data, testing for bias, and using fairness metrics across all the processes in the design and evaluation of AI systems.
Further, as AI’s prevalence grows, it is crucial to equip individuals with the knowledge and skills to use these technologies ethically and responsibly, while acknowledging their potential advantages and pitfalls. By raising public awareness and promoting education on these issues, we can foster an ethical and responsible AI ecosystem. This entails ensuring that the technology inspires trust and confidence among users, while also protecting their rights and welfare.
Businesses of today must ensure that their AI systems are transparent, reliable, safe, accountable, and operate fairly to address global concerns over privacy, ethics, and associated risks. While it is true that AI systems will always be biased to some extent, it is imperative that we should not abandon efforts to develop ethical AI. We must work towards developing AI systems that are designed to mitigate biases and promote fairness and equality. By doing so, we can harness the potential of this technology to create a better future for all, and also build trust with our customers and other stakeholders. It is time for all of us to take a proactive approach to ethical AI development and deployment, and work together to create a more responsible and ethical future for all.
This article is authored by Rakesh Prasad, senior vice president, strategy and solutions, Innover.
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