For corporate leaders, their firm’s performance on environmental, social and governance (ESG) parameters has become increasingly critical. It is not just a reporting requirement – it is also important because big investors and customers are scrutinising the record and initiatives taken by the management in these areas. According to EY’s most recent CEO survey, almost 40% of global executives state that they would like to increase their oversight of ESG factors in assessing enterprise-wise risks.In most companies, ESG discussions typically focus on issues such as pollution control, biodiversity, health and safety, business ethics and boardroom diversity. Technology-related risks and opportunities do not receive adequate attention. But three areas where corporate managements need to start focusing on now are Green Software, AI bias and Trusted Data. In the future, they will have enormous implications in all the three – E, S and G – components of the organisation.
Green software:It has come to the forefront because of the pandemic-fuelled exponential increase in cloud adoption by global enterprises. Data centres already account for over 1% of the total global electricity consumption annually. That is expected to skyrocket and become 8% of total global electricity demand over the next 10 years.
Data centres not only consume a lot of electricity, they also require a lot of water to keep cool. The environmental footprint of data centres is becoming a big area of concern around the world. Optimising hardware and using solar or other renewable sources for electricity helps in reducing the carbon footprint to an extent. But an area that can also help immensely is green software – where the software’s algorithm ensures maximum energy efficiency. This is critical because the electricity consumed in data centres is directly dependant on how efficiently software applications handle hardware resources.
In simulations conducted at the University of Washington, green software development techniques reduced energy consumption by up to 50%. Earlier this year, the Green Software Foundation – founded by corporates and non-profits including as Microsoft and Linux Foundation – took on the task of mainstreaming the sustainable coding movement. It is currently in the process of establishing green software standards and practices across various computing disciplines and technology domains. Looking ahead, sustainability officers would want to ensure that the software developed by their employees and vendors includes green practices which are subject to energy monitoring, peer benchmarking and performance reviews.
AI Bias
As corporations increasingly harness the power of artificial intelligence in everything from recruitment decisions to customer care, concerns related to AI-bias are also being flagged. Algorithmic or AI bias can have profound implications in almost any area of deployment. For instance, this bias could lead to discrimination against minorities and women, and raise questions over privacy, especially around how much data is necessary collected to make decisions. If AI is used to make decisions about people that might cause undesirable impact, how are enterprises governing that? How much information about people is it appropriate to capture? What decisions are we going to let a machine make? All this could end up in a bigger social governance issue. For example, a large conglomerate recently apologized over an “unacceptable error” in which its AI-driven algorithms categorized a video about members of a minority community as being about primates. Companies need a plan for mitigating such risks. In order to ensure social equity, it is critical to have strong governance controls for developing and deploying AI solutions.
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