Top consultancy companies use AI tools to solve their business problems. These AI tools, although highly useful, come with their own set of weaknesses. Since these AI models are trained on data, there are various ethical issues that arise such as inherent biases, maintaining data privacy, assessing societal impact of the solutions provided by these tools. Therefore, these consultancy firms must have a solid framework to focus on human-centric ethical solutions and balance innovation with responsibility.
Focus on societal good – Consultancy firms from the very beginning must focus first on being responsible as their solutions will impact human lives. Even if the AI tools they use suggest solutions that promote extreme productivity and profit, they must also assess the impact on the humans involved as in the case of job cuts. If the impact on human lives is too extreme and sudden, these solutions will only lead to a backlash in society such as bad publicity and labour strikes. Therefore, gradual changes cause less stir in society. These firms must focus on solutions that complement humans in the system rather than replace them. Certain tasks can be automated, however, human expertise is still essential for running most businesses.
Privacy of data – The making of AI tools requires vast amounts of data. Therefore, it is important to maintain the quality, integrity and privacy of the data. Data is collected from various sources such as third party data, internal company data, publicly available data etc. Therefore, all employees in the consulting firm must adhere to strict data protection norms. These norms/standards include masking identifiable data, data retention/disposal, data minimization techniques etc. These AI tools need to be upgraded by training the models on newer data to maintain its relevance and accuracy. Thus, consultants must maintain the quality of the data used and continuously refine the models.
Avoiding biases – Consultants must be aware that although AI tools are beneficial, they too are susceptible to biases. These biases occur due to various factors such as tools being trained on biassed data that reflect societal prejudices. For example AI tools are suggesting solutions that unfairly target a particular community for marketing campaigns. Consultants need to be vigilant in identifying such biases and suggest updating the AI tool used by them. Certain AI tools (explainable AI or XAI) explain their reasoning behind the results generated by them. Such tools can help consultants easily understand where the biases occur and easily mitigate them.
Promoting transparency – Consultants must from the very beginning be transparent with their clients and explain how and when AI tools were used in their processes and emphasise on the fact that AI was simply used as an aid and not as a decision-maker. However, they must maintain a good balance in being transparent and protecting trade secrets. Also, extremely technical data might overwhelm the client so it is important to focus more on actions that can be taken based on the data provided by AI. For example a consultant uses an AI tool to do sentiment analysis on social media posts. The consultant should not only collaborate with the client to understand the key metrics for the sentiment analysis but also explain how the AI tool functions.
AI is a powerful aid for most consultants and its use will undoubtedly increase over time. Therefore, it is imperative for consultants to be prepared for a world that prioritises ethical implications of these AI tools. Consultants must understand how these AI tools work, their societal implications and monitor them. This will help them mitigate risks and build stronger relations with their clients and stakeholders.
As balancing innovation and responsibility in AI is a collective effort consultants must collaborate with their clients and internal team members to build and use AI tools that have a positive impact on society.
