Balancing innovation and ethics in AI/ML

Electricity DISCOMs must ensure that consumer data privacy is not compromised even as grid digitalisation (and thus the use of AI/ML) has become inevitable to deliver efficiency, performance, customer experience and regulatory compliance.

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The increasing use of AI/ML applications in the electricity sector has raised ethical concerns regarding energy equity, accountability, transparency, and environmental impact.

Ethical concerns refer to actions that may be technically and legally compliant but 'may not be the right thing to do', if they do not meet the principles of fairness, justice and societal good. Such acts can cause reputational damage, loss of employee morale, attrition, and social backlash, and could lead to a loss of public trust, adversely affecting long-term business sustainability.

As an example, AI/ML is often used in applications such as smart metering and smart grids, which collect and analyse vast amounts of sensitive data. Electricity DISCOMs must ensure that consumer data privacy is not compromised even as grid digitalisation (and thus the use of AI/ML) has become inevitable to deliver efficiency, performance, customer experience and regulatory compliance.

Ethical concerns of AI/ML applications

Appreciation on how and where work processes could be compromised will help understand and identify ethical concerns, as explained below:

Data collection:

Smart meters collect energy consumption data at frequent intervals, providing insights into the customer energy use behaviour and lifestyle. This data, while valuable for optimising the grid, can lead to customer profiling, illegal surveillance and targeted advertisements for questionable gains. Access to energy consumption patterns could lead to discriminatory practices and even unfair energy pricing.

Data modelling: