When I returned to the office after having my first child, I noticed for the first time that all of the offices and conference rooms either had windows or non-locking doors, which left me without any safe spaces for pumping. Fortunately, I work for a supportive company that requested modification from building management to convert a small conference room to a part-time pumping room.
Shortly thereafter, the regional executives of a global pharmaceutical company came to my employer, Cimetrics, for help maintaining thermal comfort for women as part of their commitment to integrate the United Nations Global Compact and corporate social responsibility related to supporting women’s empowerment and advancing gender equality. Cimetrics’ analytical tools found that the facility’s energy reduction efforts led to exceptional efficiency but did not account for comfort variability relative to weather.
These are only two examples of systemic bias within the building industry — in this case, related to understanding the needs of female occupants — that organizations are working to correct. Many building standards developed decades ago have had only small incremental updates over the years.
For example, thermal comfort standards based on young, Caucasian, male body types (including ASHRAE standard 55) have been shown multiple times over to be biased, yet they persist as standards for building design.
As another example, historically racist housing policies have resulted in heat islands and an imbalance of energy use across communities. A recent U.S. study found that “redlined” neighborhoods, which have fewer green spaces and tree canopy, are as much as 13 degrees warmer than non-redlined neighborhoods.
There are ample regulatory drivers and utility incentives for reducing a building’s carbon footprint and embracing energy-efficient technology, but not for supporting diversity, particularly for privately held companies.
Modern “smart” buildings that aim to optimize energy efficiency and occupant satisfaction now incorporate much more sophisticated technologies than those prevalent when these biased building standards were developed, but are we learning from the lessons of the past?
There is no shortage of eye-catching headlines about how artificial intelligence can introduce or amplify bias, but evidence shows algorithms, in general, are still less biased than human decisions.
Bias is introduced into the analytics AI or machine learning through the data selection process, called training data, and through the algorithms used to process that data. A straightforward example of bias introduced through training data is biometric facial recognition that is skewed toward lighter-skinned males and therefore falsely identifies African-American and Asian faces.
There are ample regulatory drivers and utility incentives for reducing a building’s carbon footprint and embracing energy-efficient technology, but not for supporting diversity, particularly for privately held companies. What can we do to reduce bias within the built environment and create more equitable working spaces, while simultaneously working to reduce the climate impact of building and maintaining these structures?
As a female leader, I find it offensive that we must create a business case to get people to pay attention to bias and equity. That said, there is a business case for harnessing diversity and ensuring equity, as has been reflected in myriad articles and research efforts of the past few years.
Regarding the previously mentioned bias associated with temperature standards, at this time, research shows that productivity is not strongly correlated with room temperature, but productivity is correlated with the perception of comfort, and I would argue that the latter is more important for retaining high performing employees.
Moreover, energy consumption can be reduced by expanding the thermostat range during certain conditions. In short, keeping equity at the forefront of smart building development has the potential to amplify its impact on carbon reduction.
As you research building analytics and property intelligence tools that support your sustainability goals and ESG reporting requirements, make sure those tools have the flexibility to adapt to the requirements of your demographics, as well as track your performance in these areas.
It begs the question: Are you collecting the right data to ensure the behavior, comfort, health and well-being of all building stakeholders are accounted for in your decision-making? After all, what is data but a decision-making tool that allows you to be proactive and intentional in your decisions?