An Evolutionary Analysis Of Self-Drive Cars And Automated Trading Technologies

30/10/2015 7:02 PM IST | Updated 15/07/2016 8:25 AM IST

Mankind has always been evolving, but while physical evolution takes thousands of years to become visible, behavioural evolution manifests much faster. The rapid development of technology in the past few decades has already resulted in a rapid evolution of humankind's behaviour in recent years.

It is but natural that technologies that are used more frequently or for a longer duration of time have a greater impact on user behaviour. When a wider section of the populace uses the same technology and exhibits certain behavioural patterns, it helps us in developing our social perspectives and standards related to that technological usage -- the do's and don'ts, in essence, of that technological interface.

In most cases, regulatory mechanisms follow market innovations. The Wright brothers did not face any airline regulatory hurdles when they took their test flights at Kitty Hawk, and drivers in the 19th century did not have to worry about emission tests. Eventually, as regulators try and catch up with markets in this era of accelerating innovations, they often bring in additional in-built control mechanisms in the product design and specifications.

"Just like a car accident can result in collateral damage, reckless or improper trading can lead to widespread financial damages, at times even impacting the national/global economy."

In this post, I want to examine two key technologies, which I've picked because of their unprecedented potential in impacting our future - in mobility and economic activities through markets respectively.

1.Self-driving/autonomous cars: Such vehicles feature a few variations --(a) with an eligible certified driver behind the wheel ready to take over; (b) no person necessary behind the wheel (as Google envisages); (c) a middle path in between these two likely possibilities, but difficult to forecast what that this would be at this stage. These different versions can even coexist. This technology, with hugely disruptive potential, has been an area of keen business interest to many technology giants and large automobile players, and Google's self-driving car project has become symbolic of this technology.

2. Automated trading systems in financial markets: While automated cars are under various stages of trial and testing, ATS is very much in practice today, conquering trading rooms in a creeping manner, so to speak. ATS contributed to 75% of all the stocks traded in the US in 2014. For nearly a decade now, ATS and its variant "algo-trading", accounted for significant trading activities across all major markets, in both different geographic markets and different asset classes. In India too, ATS has grown in volume and value over the last few years. This has not come without problems, and additional regulations to monetary charges based on order-to-trade ratio have been tried on it. During the recent market volatility in China, there was a clampdown on algo-trading as well (regulators sometimes shoot first before realising what they are shooting at in moments of panic!).

Self-drive cars, ATS and regulatory controls

Bill Gates, back in 2000, foresaw: "It's possible that the long-term impact of the Internet could equal that of electricity, the automobile and the telephone all rolled together." We have been witnessing massive disruption as the telephone and Internet have come together; now, it is time for Internet-backed technology to interface directly or indirectly with the automobile. The concept is being pursued by pure tech companies such as Google and Apple, as well as auto-giants like GM and Tesla; Google apparently is also considering Toyota to build its self-drive cars.

IEEE, the technology trade group, identified self-driving cars as "the most promising form of intelligent transportation," suggesting that these would comprise 75% of the traffic stream by 2040. A note of caution, however, is always necessary while making long-term forecasts with immensely disruptive technologies, as experts have often found that "we tend to overestimate technology's impact in the short term and underestimate it in the long term."

Today, there's a big difference in these two technologies in terms of regulatory controls. Self-driving cars may have to go through multi-stage regulatory clearance process, whereas ATS has already made large inroads and regulators are now struggling on how to control its potential misuse (though defining this misuse is a challenge in itself).

It is wrong to think that safety standards apply only to self-driving cars that operate on public infrastructure, while ATS can grow unchecked as we all are free to do whatever we want with our money as long as it's legal.

Just like a car accident can result in collateral damage, reckless or improper trading can lead to widespread financial damages, at times even impacting the national/global economy, and thereby broader society and the livelihood of millions. Lately, we've seen that the speculative economy has been driving the real economy and not vice-versa. The greed culture associated with Wall Street and other financial markets seldom takes into account this potential for damage. While ATS cannot be blamed for this culture it does speed up and magnify hugely the problems that have existed since markets evolved.

Widespread adoption of technology often provides an opportunity in the end-to-end business process reengineering, known as BPR among management consultants. The observation made by Google recently, that the most difficult hurdle for self-driving cars are those with drivers -- any self-driving car can be made to follow the rules to a tee all the time whereas none of the drivers we know in real life probably do that.

"These two technologies highlight the different challenges we face -- one has physical rules and attributes, the other is driven by "greed" and is, therefore, ill-defined, making the task of its regulation and control even more difficult."

Dmitri Dolgov, head of software for Google's Self-Driving Car Project, said that the key learning of his team from the project has been that the human drivers needed to be "less idiotic." There is a case of inter-dependency here.

The challenge with technology here is visualising all the possible usual and unusual scenarios on the road. But it cannot predict when another human driver acts in an unusual way, be it in crossing a signal or in maintaining a safe distance.

Similarly, with or without ATS, reckless and manipulative trading is a fact of life, but the use of technology can magnify and multiply the same many times. The pertinent question to be asked here is: did financial regulators miss that opportunity when ATS was silently creeping inside trading terminals over the decades, first in the form of technical analysis and then as quantitative finance? Some might suggest that regulators could have also cleaned up the massive leveraged positions to the derivatives that have been introduced as "financial innovations" by some, but which have been described by legendary investor Warren Buffet as "financial weapons of mass destruction".

Now imagine that ATS adoption means such financial weapons of mass destruction are left to machines without any human interventions - or just think back to the infamous flash crash of 6 May, 2010. At the same time, there is also merit in the school of thought that short-sellers, derivative-players, leveraged traders and algo-trading bring in much-needed balancing forces in the market excesses. This balance is necessary in the longer term, but in the short- to medium-term, markets remain risky. That cannot be the case for self-drive cars operating on today's roads and their "idiotic" drivers. Before such cars reach critical penetration in the coming years, many other on-the-road hurdles and regulatory questions are likely to come to light.

The problem with ATS still remains in spite of more than 75% adoption in key markets and asset classes. The charges against Navinder Sarao, arrested in April 2015 related to that 2010 May flash crash, are something that any trader knows to be widespread in any financial markets. One can pick any one or two wrongdoers from time to time out of hundreds in order to discipline the market known for its "greed" and ill-defined rules, due to natural complexities. There surely is merit in Sarao's claim, "I haven't done anything wrong apart from being good at my job."Today, a rogue driver operates much as a rogue trader does, and often gets away with it - after all, there's no paper or electronic trail.

Sarao's algorithm that worked on "cancel if close" spoof orders, feigning action against intention, borders thinly between illegal manipulation of markets and deft trading. A shopbot, or comparison shopping website, also collects information and shares; and any user may cancel his/her order at checking counter if a much better deal appears on such a shopbot. Players can outcut each other's prices following such a system. When the action is genuine and when it is manipulative just because of a systematic software is difficult to disentangle. More importantly, the symptom, as Sarao was quoted: "Lol, guarantee if I switch on my computer I'll see the same people breaking all those rules, day in, day out."

These two technologies highlight the different challenges we face -- one has physical rules and attributes, the other is driven by "greed" and is, therefore, ill-defined, making the task of its regulation and control even more difficult. As Gordon Gekko struggled to define greed back in 1987 ("Greed, for lack of a better word, is good. Greed is right. Greed works. Greed clarifies, cuts through, and captures, the essence of the evolutionary spirit. Greed, in all of its forms; greed for life, for money, for love, knowledge, has marked the upward surge of mankind"), regulators must continue their struggle to define what spoofing or manipulative trading actually is.

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