Sway is a thoroughly researched and comprehensive look at unconscious bias and how it impacts day-to-day life, from job interviews to romantic relationships to saving for retirement. It covers a huge number of sensitive topics – sexism, racism, ageism, homophobia – with tact, and combines statistics with stories to paint a fuller picture and enhance understanding. Agarwal also clearly delineates theories with a solid grounding in science from musings which have yet to be proven, presenting references for each argument made and allowing the reader to make up their own minds. Science is ever-evolving, and sadly this is an under-researched field.
Sway is split into several sections. The first, ‘Hardwired’, covers basic neuroscience and psychology – how our brains create an image of ourselves, the world, and how the two fit together. It unravels the pathways involved to give a grounding to the lay reader. I have a neuroscience background, so whilst this was interesting I can’t comment on its accessibility to someone new to the field. However, Agarwal includes several diagrams to illustrate her points, and I imagine these will be very useful to those trying to picture the concepts she describes.
The second section, ‘Smoke and Mirrors’, covers the ways in which our brains reinforce biases and prevent us moving past them. This was fascinating. It covered things like hindsight bias – believing after something has happened that we knew would happen from the start, even though we actually had no or very little idea. These are concepts which we rarely consider day-to-day but are incredibly important for acknowledging our own limitations and mistakes. We cannot confront our own biases and blind spots unless we’re aware that they exist. Agarwal includes plenty of examples and anecdotes to prevent the material becoming dry, again citing all her sources so that those interested can read further.
The third section, ‘Sex Type-Cast’ covers what everyone thinks of when they think of bias – prejudice, from racism to sexism to homophobia. It also covers things that people might think of less – fatphobia, ageism, and discrimination based on ‘beauty’ or conventional attractiveness. Agarwal combines scientific data with her own polls carried out on Twitter, with some rather interesting results. After all, one of the well-known biases in science is research bias – those involved in research studies, including those on bias, are not representative of the whole population, but instead just of the population willing to get involved in research. This is a different group to those happy to spend a few milliseconds clicking on a Twitter poll. Agarwal doesn’t claim huge scientific accuracy to her Twitter poll data, merely including it as a point of intrigue – it supplements the more conventional sources very well.
The final section, ‘Moral Conundrum’ looks to the future and the impact of technology on bias. Technology is claimed by many to be the solution to bias – why would a robot care about race? The answer, of course, is that robots care about race because the humans programming it do, and the data sets they are trained on have their own intrinsic biases. There is a chapter in this section called ‘Good Intentions’ which covers the incredibly contentious topic of how trying to reduce bias can end up increasing or reinforcing it, which should be mandatory reading for everyone. Agarwal covers the issue masterfully and without judgement, merely presenting the facts and highlighting the importance of education and continual learning. Being completely unbiased is impossible – all we can do is continue to learn from our mistakes, learn our own biases, and act on them.
Overall, this is an excellent book – well-researched, informative without being dry, and highlighting some incredibly topical issues. Recommended for everyone.
Published by Bloomsbury
Hardcover: 2nd April 2020