Can Diversity Ensure that Technology is used to Benefit Society? It might not be immediately obvious what diversity has to do with Artificial Intelligence, ethics in quantum computing, laser art, or quant based investment funds, other than that they are all being increasingly recognized as valuable to their individual field. This article attempts to demonstrate the correlation of diversity and positive results in a whole host of familiar and less familiar areas of society and business. Health warning: the correlation and causation trap has been duly heeded and any correlation should be read with the caveat of the following amazingly hilarious joke: “I used to think correlation implied causation. Then I took a statistics class. Now I don't.” “Sounds like the class helped?” “Well, maybe.” Gender Diversity and Big Data – The Fund Management Edition Is it important that the investment industry ensure that there is a diverse representation of women in “Big Data” fund management? The backdrop to this question (spoiler alert – the answer is yes) will be the Goliath of investment management, BlackRock. BlackRock led the quant investment leap (pun intended) in 2017 with a project code named “Monarch” which entailed shifting billions of dollars to their computer powered Systematic Active Equities arm in San Francisco, firing a few active fund managers in the process. The SAE team at BlackRock analyse Big Data using technologies like machine learning and use proprietary techniques to exploit fundamentals information in an attempt to constantly improve investment outcomes. As ever in the perpetual race between active and passive investment the jury is out as to who will win the inflow competition in the long run, not to mention the returns. 2018 has seen a deceleration of net inflows into passive mutual funds and exchange traded funds with a 44% slump in the first half of the year from the same period in 2017, according to Morningstar. Yet, sovereign wealth funds, endowments, charities, trusts and pension funds alike are relying to an ever greater degree on passive funds in one guise or another; the next step could be the quant driven funds the likes of SAE. The sector clearly need to ensure that gender diverse leadership is captured; the investment managers in SAE and similar setups are still actual human beings with normal human biases as well diverse ideas and thought processes. They will conduct the research into new ideas, ensuring that models are fine tuned to the current market environment, challenge the findings of the models, all to provide a stable risk return for investors that still hopefully beats the purely indexed equity allocations. And, where you need people you need diversity.
Although it is notoriously difficult to prove a positive correlation effect between diversity and organisational performance, one example of a link between fund performance and gender diversity in particular provides at the very least an interesting starting point. The research paper Gender, Overconfidence, and Common Stock Investments[1] showed that women are less likely to engage in excessive stock turn-over than men. The paper evidenced that over the measurement period men traded 45% more than women and that the over-trading reduced men’s returns by 2.65% a year versus a reduction of 1.72% for women. Apply that percentage on a few billion dollars and you got yourself a case for diversity. There will be similar examples that show the opposite performance results in other areas of managing funds; clearly we need both women and men as well as wider diversity such as diverse socioeconomic backgrounds. May I order some Artificial Intelligence for my next upgrade Human 2.0? AI has moved swiftly from concept to reality with several implications for society as a whole - at the very basic level the very real outcome of our human traits of unconscious biases being systemically worked into the next generation big data collections. Interestingly, if we think even further into the future a different albeit tangible risk is that AI indiscriminately carries out instructions set by their human architects; are we capturing enough diversity in teaching the next generation of computers ethics? Implications of not getting ethical machine learning right is a peril explored for example in the “Economist 1841” article Teaching Robots Right from Wrong[2]. Considerable consequences could arise as we entrust technology with, for example, the decision of the direction of a missile, as well as the gathering of data for reconciliation missions and diplomacy in peace keeping efforts. We are not yet positioned well enough to capture diversity within AI ethics, driven historically by low levels of diversity in STEM education and research. Global institutions such as Barclays and Goldman Sachs have targeted efforts to bring more gender diversity into areas such as programming, but we need to do more and fasten the pace in order to capture the opportunities and mitigate the risks. Next stop - Quantum Computing Although there is a task force in the EU who are dedicated to how the financial system among others will cope and defend against quantum computing used for malevolent gains, we are merely at the infancy of protecting against quantum decryption in the future. Other uses and effects will be evident in areas such as voter mapping that can drive election results and analyzing DNA-sequencing to develop more efficient drugs. Quantum Computing and machine learning will additionally be able to determine outcomes of the cost-benefit analysis of healthcare intervention such as who gets to be treated with what type of drug, with life changing implications for both sick and healthy. Diverse leadership quite clearly needs to continue to be reflected in our work with quantum computers as this technology will shape society in the years to come. Life imitating art, or the other way around Finally, the world is of course not only concerned about returns and losses nor merely about right or wrong, it is also shaped through art which is becoming ever more intertwined with technology; Russian artist Dmitry Morozov creates art based on sensors which pick up air
pollution and transforms them into colour patterns depending on their chemical compound. Apparently exhaust fumes are particularly colourful. Or scientific visualization artist Donna Cox whose art helps scientists visualize and interpret complex data, as well as bringing astrophysics to the masses by her installations. We like difference! As warned at the start of this article, I am not exactly on the fence about this one; technology need diversity to win society the race. I experience constantly how competitive the fight can be for a diverse talent pool can be but in order to capture the opportunities that technology will afford us, we have to ensure that diverse leadership is the norm rather than a lauded goal. Society will need progressive thinking within all spheres of technology and we simply need representation from the whole gender spectrum for it to be achieved. I think the next HR roundtable I arrange will be tech and data centred, let me know if you are interested and I will organize!
[1] Brad M. Barber and Terrance Odean, 2001 [2] https://www.1843magazine.com/features/teaching-robots-right-from-wrong