Sport

The New World Upon Us

This is the 45th installment of Lighthouse, my monthly column for BLink, a supplement of the Hindu Business Line.

Alpha Zero’s achievement in chess is staggering. It showcases a quantum leap for Artificial Intelligence.

If there is one thing that sets human beings apart from other species, it is this: we think too much of ourselves. Just because we lucked upon opposable thumbs and a powerful brain, both of which allowed us to dominate other species, we behave as if we are masters of the universe. It’s pathetic. We’re bawling babies in front of a bacterial onslaught, and we will soon find ourselves inadequate in front of machines that we ourselves will make. It is time for humility.

A few days ago, Alpha Zero beat Stockfish. We humans talk about Ali-Foreman and Federer-Nadal and Fischer-Spassky, but the most momentous match in human history might well have been the chess match between these two machines. But first, some context.

Here’s the Artificial Intelligence context. In 1950, when AI was in the realm of science fiction, Alan Turing came up with the Turing Test. Wikipedia defines this as “a test of a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.” So if you’re having a text conversation with a party you cannot see, a machine would pass the Turing Test if you do not realise that it is a machine. I would hold that AI has achieved this easily, although many humans would probably fail. (Check out Donald Trump’s Twitter feed.)

Here’s the chess context. Until the early 1990s, the thought of a computer beating a human in chess was laughable. But technology progressed quickly, and in 1997 a machine called Deep Blue beat the then-World Champion, Garry Kasparov. Computers soon left humans far behind. Today, a program on your smartphone can thrash the best player in the world.

Now, you’d imagine that this would mean the end of chess. Everyone would use computers in their analysis and pedagogy, and we’d all start playing like machines. But exactly the opposite happened, and chess was instead enriched.

There was once a study that aimed to see how many moves a grandmaster and a novice could think ahead in a game of chess. The answer was that they saw the same number of moves ahead, but the GM saw the right ones. Learning chess is less about calculation and more about pattern recognition and heuristics. The more you play, the more patterns you learn to instinctively recognise, with an understanding of how they interact with other patterns. A strong player can glance at a position on the board and understand its salient aspects.

And then, the heuristics. Heuristics are simple rules that allow people to make decisions. For example, a chess player will be taught that it is important to occupy the center early, to take her king to safety by castling, to develop her pieces as much as she can, and so on. Now, humans cannot possibly calculate everything on the chess board. (The number of possible positions in a 40-move game is greater than the number of electrons in the observable universe.) So they use shortcuts – or these heuristics.

All humans learn chess by learning heuristics. These have evolved over centuries, and are a common body of knowledge that every player has to learn to reach a certain level. The famous Soviet School of Chess was the embodiment of this. Given this common body of knowledge, chess players actually played in a similar way, with individual style appearing on the margins.

Computers did not need heuristics, because they had the computing power to actually calculate every move and every position. (This is called ‘brute force’.) This did not make chess more homogenous, but less, as computers looked beyond the set of heuristics that were instinctive for players. This meant that the new generation of players who used chess programs as an analytical tool were no longer bound to the dogmas of the past, useful as they were. All the principles earlier generations had learned had exceptions, and all the exceptions could be explored using these programs.

As a result, the current generation of players has more stylistic variation than ones before. Younger players think about the game in unique ways that older ones can’t fathom, and is outside their playbook. And while all top players use programs like Stockfish for analysis, none of them plays games against it because Stockfish would thrash them, and it would be too demoralising. It’s like trying to race a car.

So what did Alpha Zero do? Well, Alpha Zero was built by Deep Mind, an AI division of Google. It is a self-learning program, and the rules of chess were fed into it, but nothing else. No opening databases, no heuristics. It played against itself for four hours to learn the game. Then it played Stockfish in a 100-game match. Alpha Zero won 28 games, and the rest were drawn. After four hours of learning, it beat a chess program into which years of development had gone.

Astonishingly, Alpha Zero achieved this by playing like a human. While Stockfish examined 70 million positions per second, Alpha Zero looked at only 80,000. While teaching itself chess, it discovered, developed and then used heuristics that seem to go beyond the ones humans discovered. For example, human are taught not to move the same piece multiple times in the opening when others lie undeveloped. Alpha Zero did this again and again, favouring activity over development. It also made long-term positional sacrifices, with no immediate gain, which machines otherwise do not do.

The games released by Alpha Zero are spectacular. Alpha Zero plays like a human, but an enhanced human. The grandmaster Peter Heine Nielsen, Magnus Carlsen’s coach, told chess.com: “After reading the paper but especially seeing the games I thought, well, I always wondered how it would be if a superior species landed on earth and showed us how they play chess. I feel now I know.”

The implications of the Deep Learning that Alpha Zero demonstrates are fantastic and unfathomable, and not just for chess. AI is already embedded in our lives – your smartphone would have seemed like science fiction in 1990 – and will become more so. It has become fashionable to be worried about AI, but I am optimistic. Technology will make us all better versions of ourselves – and that journey begins by accepting that we aren’t all that awesome to begin with.

A Few Thoughts on Match Poker (and the Match IPL)

A couple of weeks ago, I took part in the Match IPL, playing for Goa Kings. The IPL here stands for Indian Poker League, and it follows a similar franchisee model as cricket’s IPL. I don’t play poker these days, having retired a couple of years ago, but a good friend, who was the mentor of this team, asked me to join, and I thought it would be fun.

Also, one important reason I joined was because this was a new format of poker, and I wanted to set myself the intellectual challenge of understanding it and optimising for it. When I was active, I was mainly a live cash game player, with decent tournament results in the Asian circuit. But this format of poker was different in key ways from both cash games and tournament poker.

The Format

Match Poker is a format played by teams. It’s explained here, but I’ll sum it up briefly. Let’s say there are seven teams with seven players each. They play each other on seven tables, with one player from each team on every table. Also, there’s one player from each team on every seat. So if you are on seat 1 on table 1, all the other tables with have players from other teams on seat 1. So every team will have a player on every table and every seat.

The idea is that the same hand is then dealt across tables. So all teams play the same hand from every position. At the end of every hand, a team’s chips across positions are added. The team with the best chip count gets 7 points, the next team gets 6, and so on down to 1. The chip count is reset, and all teams start the next hand equal in chips. At the end of a certain number of hands – 200 in the case of Match IPL – the team with the highest points (not chips) wins.

The Question of Luck

According to the guys who thought this up, this format ensures that “the luck element in conventional poker via the ‘random draw of cards’ has been removed.” In fact, the Match Poker guys claim that because this removes the element of luck, that makes poker a true sport. They are using this rationale to get Match Poker into the Olympics.

This claim is both moot and false. It is moot because of two reasons, one small and one big. The small reason is that all sports do have an element of luck, and that’s doesn’t make them less of a sport. The big reason is that even though poker has a greater quantum of luck than other sports, it is still a game of skill in the long run. What happens in any one hand is largely luck, but given a large enough sample size, skill will make the difference.

Also, the format doesn’t eliminate luck entirely because there is still much variance in the game. Let’s say you are the best player in the best team. You hit a set, and maximise pot size to get your opponent with top pair all in. No other team manages this. But then your opponent hits a runner-runner full house, as he will 2% of the time. Your team played the best here – but you will come last, and the team will get just one point. This is luck, and it doesn’t matter in the long run because it all evens out. But you need a decent sample size of hands for the skill to show. 200 hands – or even 2000, or perhaps 20,000 – is not enough.

How Match Poker is Different from Poker

Although Match Poker is set up like a deep-stack cash game, it is different in two fundamental ways. One, the unit of measurement here is not chips, but hands won. Two, you are not playing against your table, but against all the other players sitting on your seat (and dealt the same hand) at the other tables.

Let’s start with point one: chips don’t matter. Teams are not ranked according to how many chips they win in a session, but how many hands they win. This is the opposite of regular poker. A study on online sites showed years ago that the players who win the most hands lose the most money. A good cash game player will lose more hands than he wins, but will win more when he wins than when he loses, and be overall profitable.

An illustration of this is set-mining. I will always play 44 preflop, if there is just one raise, and I will hit my set only one in eight times. Seven times I don’t hit the set – but the one time I do, I make enough money to compensate for the times I folded. But in Match Poker, that doesn’t matter. Point two explains why.

Point two: You are not playing against the table, but against other players on your seat. Let me illustrate this with the set-mining example. Let’s say you get 44. You fold preflop, while you know all the other players on your seat will call. Seven out of eight times, they will fold on the flop, and because you saved that preflop call, you are first on your seat. One time you are last. Assuming ceteris paribus (all other teams and players get equal results in other seats), your team gets seven points seven times and 1 point once, for a total of 50 points in eight hands. All other teams get 24.3, splitting the remaining points. Thus, while set-mining with small pairs is profitable in regular poker, folding them preflop is profitable in Match Poker. It is +EV in this format, or as I’d call it, +MPEV.

The same logic holds for speculative hands like suited connectors. If other teams are likely to play those hands, and they lose more than 50% of the time, your profitable move is to fold. Ditto for chasing flush draws on a flop. Remember, pot odds and chip EV don’t matter, because this is not traditional poker. So a lot of moves that +EV in regular poker are -MPEV.

Three Rules

With this thinking in mind, I formulated three thoughts that I wanted my teammates to think before every hand.

1. I am not playing this hand against the table. I am playing it against other players on this seat.

2. What are the players on this seat likely to do with this hand?

3. Will I win this 50% of the time?

If you have a speculative hand that your opponents (the players on your seat) are likely to call, and that hand will lose more than 50% of the time, then it is +MPEV to fold it right away.

The Strategy

So here’s what the points system means. Teams get from seven to one points for every hand. The average is four. It’s all zero-sum, so teams win what other teams lose, and the amount won is equal to the amount lost. You might have one team winning chips on a given hand and six teams losing, in which case the team that lost the least gets six valuable points. You might have one team losing and six winning. But generally, if you fold every hand, you should get around 4 points per hand. (Simulations validate this, FWIW, with the limited data I had from a previous event.) The team that won Match IPL won with 821 points from 200 hands, or 4.1 per hand. Three out of seven teams finished above the mean (800).

Now, obviously, folding every hand does not win you the whole thing. What I considered the optimal strategy was to fold all speculative hands and medium-strength hands, and push all value hands hard, but to define these value hands tightly. Also, profit in poker comes not just from value hands but value spots. Position matters, and there is much value to be had if you can outplay people in a button-vs-blinds dynamic. I’ll come back to this later: our initial strategy was based on not thinking too hard about spots and focussing on hands.

Instead of playing 20% of hands, as we otherwise might, we decided to play 5%, fold 95% and see how it goes. We would fold all speculative hands, all medium-strength hands (like KJs in early position) and we would also fold strong hands in multiway pots where our chances of winning are less than 50%. (Remember, in this format, pot odds don’t matter. 50% is the magic number.) We even made a hand-chart by position for our players to memorise. This was a new format and we were all beginners here, so that made sense.

We started the tournament disastrously. There were 8 sessions of 25 hands each, and in our first session, we were hit by variance. The problem was Seat 1. Our man in Seat 1 made a series of correct folds, (correct in terms of MPEV), and those hands kept hitting. Sets hit. Random hands hit trips. Connectors hit straights. Hands that would win one in eight or 15 or 25 times kept hitting. And other teams played those hands, and got points for them. We got on the wrong side of variance, which happens. But with just 175 hands left in the session, could we recover?

We remained in the bottom half of teams through that first of two days, though I was topping the individual charts at the end of day 1. In fact, I topped the individual charts at the end of 5 sessions out of the eight, but fell short of winning the MPV at the end of it. And this brings me to the problem of the individual leaderboard.

I assumed that the individual leaderboard would be calculated the same way as the team leaderboard: they’d see how you did against the players on your seat, and assign between 7 to 1 points for each hand. I assumed I led for so long because I was playing optimally. But I later found that this was actually being decided on total chip counts – ie, just like normal poker. (They were assigning differential points based on how you outplayed guys on your seat, but it was still looking at overall chips, not hands won.) Thus, doing well in the individual charts had no correlation to how well you played for your team. One was calculated as per chips, the other was as per hands won.

Value Spots

So given our strategy, how the hell was I leading for so long? Well, this brings me to the issue of value spots. You not only have to play value hands strongly, but also keep your eyes peeled for value spots. When everyone folds to you on the button, that could be a value spot if the blinds are passive. If you are in the small blind against a button open, that could be a value spot if you get him to fold. These are also high-variance spots, but spots you could win more than 50% of the time, so you have to use your judgement. (In this format, btw, I’d define a Value Spot as a spot where you can win the hand more than 50% of the time, regardless of the actual hand you have.)

I took the liberty of searching for such spots against the guy on my left, an excellent cash game reg who would attack my button from his small-blind. I couldn’t simply fold all my buttons, because players on my seat would probably win there a fair bit. So I had to play back at this guy. We had a 3b-4b dynamic going on, and in one hand I stacked him with Q7s against 96. (It went raise-3b-4b-flat, flop came Q96, with 7 on the river. Standard spot.) In another hand on the second day, in another 3b-4b spot, I took an all-in call on the river with A-high, in a spot where he would check-call all showdown hands because I was guaranteed to bluff. His range was polarised, as I thought, but he happened to be bluffing with bottom pair and I lost. The call was correct anyway, because once I have put in enough chips to ensure that I am last on my seat, there is nothing to be lost going all the way. (Ceretis Paribus, again.)

Again, the key rule with value spots is simply whether you’ll win more than 50% of the time, and what your opponents do doesn’t even matter here, because you’ll either get 7 points or 1. You beat the average by winning more than 50%.

So, the optimal strategy is to fold a lot, including all speculative and medium-strength hands, push all value hands hard (if you get coolered, so will everyone on your seat) and use your judgement for value spots. We started off unlucky, some panic set in, and we ended fifth. I slipped off first place in the individual leaderboard, ending 11th, but that was a chip-count thing. (If they calculated that the same way as team points, I’m sure I’d be higher.)

What was worse was that the winning team, after getting lucky on day 1, followed my strategy on day 2 and were thus uncatchable. One of them mentioned that they looked at my hand histories at the end of day 1 as I was leading the individual leaderboard, and their chief strategist is a close friend to whom I had boasted that I had cracked the optimal strategy. They didn’t necessarily get it from me, and this stuff isn’t rocket science to figure out. The fact that they shifted to my strategy on day 2 (one of them folded 24 out of 25 hands in one session, I heard) is intellectual validation that my ideas were correct – though I would have preferred monetary validation. SAD!

(No other team seemed to have figured out the strategy, by the way, with the team that came second playing a LAG style that is perfect for deep-stack cash games but sub-optimal for this format.)

For what it’s worth, I don’t intend to play this again, which is why I am being free with my thoughts here. I expect all the teams to read this, though, thus adding a metagame element, and making their subsequent search for value spots that much more fascinating.

The event was glitzy, with drone cams and so on, so watch it on MTV if you can. I haven’t seen it yet, and I am sure that if I do, I’ll be even more determined to resume my Keto diet.

Also read

The archives of Range Rover, my old poker column for the Economic Times.

The Five Commandments of Poker, an episode of the podcast Mera Kaam Poker that features me.

Why Do You Love Potholes?

This is the 43rd installment of Rhyme and Reason, my weekly set of limericks for the Sunday Times of India edit page.

KAUR BLIMEY

On Thursday, I watched Harmanpreet Kaur
Play a knock that left me wanting more.
What a game? What a show!
And now I want to know
Why had I not heard of her before?

POTHOLES

I hauled a neta over the coals.
I said, “Bhai, why do you love potholes?”
He said, “Bro, they’re a dream.
They’re my revenue stream.
Kickbacks from repairs are my bankroll.”

Two Old Men

This is the 41st installment of Rhyme and Reason, my weekly set of limericks for the Sunday Times of India edit page.

AFFECTION

Netanyahu was looking happy.
He said, “Modi gave me a jhappi!”
I said, “Bro, you must chill.
Otherwise, Modi will
Take it further, and give a pappi.”

FEDERER’S LESSON

MS Dhoni has turned thirty-six.
Some ask, should he still be in the mix?
Well, like that old codger
By the name of Roger,
Maybe he has not run out of tricks.

A Protest. Then A Celebration

This is the 40th installment of Rhyme and Reason, my weekly set of limericks for the Sunday Times of India edit page.

NOT IN MY NAME

When the country is torn, bit by bit,
Those who are silent are complicit.
If it fills you with shame,
Then shout: “Not in my name!”
Shake your apathy. Do not submit.

SMRITI MANDHANA

Indian cricket’s got a new face,
A left-hander with timing and grace.
Her strokeplay, by and by,
Makes me wonder why I
Thought women’s cricket was commonplace.

Procrastination (and Kumble vs Kohli)

This is the 39th installment of Rhyme and Reason, my weekly set of limericks for the Sunday Times of India edit page.

PROCRASTINATION

Do you know what’s my greatest sorrow?
Time is something you cannot borrow.
So the days go by,
As I watch paint dry,
And sit here waiting for tomorrow.
 
K VS K

Kumble said, “Get me out of this jail.
It’s so sad that I’m the one to bail.”
Kohli said, with a groan,
“It’s my house they will stone
When we lose. That’s why I should prevail.”

One Tax To Rule Them All

This is the 35th installment of Rhyme and Reason, my weekly set of limericks for the Sunday Times of India edit page.

GST

The Goods and Services Tax is here.
Most other taxes will disappear.
One massive overhaul.
One tax to rule them all,
Till the slabs and exemptions appear.

OVERDOSE

So much cricket is driving me mad.
The IPL had seemed just a fad.
Cricket is such a bore,
I will watch it no more.
(Except today’s final, let me add.)

*

Also hear: Episode 3 of my weekly podcast, The Seen and the Unseen, with Devangshu Datta, which was about the GST:

The Winning Mantra for this IPL: Attack, Attack, Attack

This is the third installment of The Rationalist, my column for the Times of India.

When the Indian Premier League began a decade ago, my fellow cricket purists bemoaned what they called a tamasha version of the game. I was an enthusiast, though. I was baffled that so many people felt a three-hour game was too short to be taken seriously as a sport. Football lasts 90 minutes. Hockey is an hour. Tennis, badminton, basketball matches all tend to be shorter. None of them lack nuance or complexity or drama, and are rich in strategic and tactical options. So why should T20 cricket be any less than that?

I expected T20 cricket to have a number of positive effects, and it has delivered on all those counts. It has widened the pool of players who can make a healthy living by being professional players. It was broadened the audience for the game, as many more people are willing to spend three hours watching the game than than they would be to spend five days. And it has enriched the other forms of the game.

Cricketers are now fitter than ever before, and batsmen and bowlers alike have developed tools in their arsenal that were not necessary before. The shorter format demands greater urgency, and players have to approach the game differently. Intent leads to ability. A batsman who needs to play an aggressive stroke to every ball will develop a better repertoire of aggressive strokes. A fielder who is desperate to save every run he can will be fitter, and will have better technique. Bowlers, in turn, will have to adapt to more aggressive batsmen by pushing the limits of what they can do. (And indeed, contrary to early stereotypes, T20 cricket isn’t a bang-bang slog-fest, and bowlers remain matchwinners.)

This has percolated down to Test cricket. Nostalgia makes us overestimate the past, but in terms of pure skill, modern greats are a league above the legends of the past. This is not because they are inherently more talented or hard working. It is because, as an economist would say, the incentives are different. T20 cricket demands more from them, and they have adapted.

I consider T20 cricket to be a separate sport, all on its own, and in that light, the last ten years have been fascinating. We have seen a new sport evolve out of the framework of an old one, and every year has seen the game develop rapidly. The key strategic development has been in the structure of the game itself.

Teams initially came to T20 with an approach transplanted from one-day cricket. Every innings had three broad phases: pinch-hit, consolidate, slog. But this was a mistake. In ODIs, teams have around seven batting resources for 50 overs. In T20s, they have the same number of batting resources for 40% of the overs. The reduced overs mean that the opportunity cost of a dot ball goes up, and the opportunity cost of a wicket goes down. The risk-reward ratio changes, so batsmen should attack more.

In fact, they should frontload, as I like to say – they should begin with attack, and attack all the way through. A team that bats through 20 overs losing only three wickets has probably wasted resources, given the batsmen waiting in the pavilion. They should have attacked more; every over can be a slog over.

Some teams understood this, like West Indies in the last T20 World Cup, or Sunrisers Hyderabad last year. But many teams still don’t get it. I wrote before last year’s IPL that teams are underestimating par scores and not frontloading, so anyone into cricket betting should blindly bet on the team batting second, as the team batting first will score less than optimally. That’s exactly what happened. Out of the first 14 games, 13 were won by the side chasing in an average of 17.2 overs, with an average 6.6 wickets in hand. (Teams adjusted in the second half, so follow that advice this year only for teams that don’t frontload.)

The most important statistic for a batsman, thus, is his strike rate. We might consider a strike rate of 125 healthy by ODI standards, but it is pathetic for T20s. A team batting at that strike rate would make 150 runs, which is well below par. A batsman playing at that strike rate is, thus, a liability to his team – the more balls he faces, the more he is letting them down. (As there should be no consolidation or innings-building phase in T20s, there is no ameliorating factor over a season.)

So here’s one stat you should keep your eye on this season: a batsman’s season-long strike rate minus the overall par-score strike rate (for a par score of 180, that would be 150). Let’s call it the Varma Number. If it is negative, the batsman has failed.

Earlier pieces by me on this subject:

Opportunity, choice and the IPL (2008)
The Lesson From This IPL: Frontload Your Innings (2014)
Never Mind the Bullocks, Here’s the Lamborghini (2015)
The New Face of Cricket (2015)
What Cricket Can Learn From Economics (2016)
National Highway 420 (and the EV of Aggressive Batting) (2016)

A Top Edge (and a Brain Fade)

This is the 30th installment of Rhyme and Reason, my weekly set of limericks for the Sunday Times of India edit page.

SHERRY

Navjot Singh Sidhu was in a fix.
No party wanted him in the mix,
Till Congress took him on.
Good fortune came along.
His top edge went all the way for six.

CRICKET

One day, in my school, there was a raid.
A boy was caught cheating in tenth grade,
But he was remorseless.
He said, with great finesse,
“It was nothing more than a brain fade.”

Embrace the Technology!

This is the 36th installment of Lighthouse, my monthly column for BLink, a supplement of the Hindu Business Line.

At the very moment you read this, there is a Test match going on and two batsmen consulting out in the middle about whether they should use the DRS.

“Was I really lbw? Should I refer? Do you think it was missing?”

“I don’t know. But whatever you do, don’t look at the pavilion. Control your neck. Control it. Hold it if you have to. Here, I’ll hold it for you. Control!”

Crack.

The big cricket story of last week, somehow, was not India’s excellent comeback in the Test series against Australia, but the DRS controversy. Batsmen are not supposed to look at the pavilion for advice when deciding whether or not to go for a decision review. Those are the rules, Steve Smith broke the rule, and it was fair enough that he was asked to leave the field of play. But the rules themselves are ridiculous.

I’ve been ranting about this for years, and still these people don’t learn. You would think no one reads me. Gah. Anyway, because I care about you, here, once again, are my thoughts on technology in cricket. And in life, which, by the way, is futile. (I don’t shy away from the big questions.)

First up, a question: why do umpires exist in cricket? After all, cricket is about batsmen batting, bowlers bowling and fielders fielding. No one goes to a ground to watch an umpire umpire. Well, umpires exist purely as a means to an end. They have to take decisions about whether a batsman is out or not, and lubricate the action in the game by communicating to scorers exactly what is going on. A secondary function is to step in if there is physical conflict, and to maintain decorum. Their job is not to be the action, but to keep the action flowing smoothly.

In other words, umpires are a technology.

Think of anything that is a means to an end as a technology. Umpires are a conventional technology for arriving at the right decisions on a cricket field. Now, the last couple of decades have seen rapid upgradations to pretty much every other technology there is. And so it is in the case of cricket. The decision-making mechanisms in cricket have been enhanced with new technologies meant to supplement (and not replace) the umpires.

The most significant of these is Hawk-Eye. Umpires, being human (as of now), are prone to all kinds of optical illusions, such as the parallax error, which impede their decision-making ability. Hawk-Eye, in every respect, makes better decisions than an umpire can. (And it makes them in real time – the time-consuming replays you see you on TV are only for the benefit of viewers.) But for the longest time, luddites fought the use of Hawkeye in decision-making, which led to the ridiculous situation that everyone watching a game had accurate information about whether a batsman was out or not – except the bloody umpire. It was ridiculous.

Cricket authorities have since become more open to the use of technology, but not enough. They almost seem to use it grudgingly. Consider DRS, for example. If the idea of the technology called umpires is to make correct decisions, and there is more technology that will lead to even better decisions, then why don’t we use it as much as possible? Why should DRS appeals be limited for a batting side? Why should every dismissal not be reviewed as a matter of course? Reviewing a dismissal would not take more time than a batsman walking back to the pavilion, so this should be a no-brainer.

Steve Smith wouldn’t be so embarrassed then, eh?

But really, the larger issue here is that the world is changing rapidly, and our minds are not adjusting fast enough. It’s not just cricket. As a species, we don’t have enough clarity about means and ends. For example, just as umpires are a technology for making correct decisions on a cricket field, consider that animals are a technology for growing food. And now that scientists have figured out a way to grow meat in labs without sentient animals being involved, they may soon be an outdated technology, at least for this use case. That might lead to goats going extinct. (Not puppies, though, because puppies can be hugged.)

Equally, hugs are a technology for oxytocin generation. Romance is a technology for the way it makes us feel and the chemicals it releases. If we could pop a pill and feel the same way, would we bother to fall in love, or hug or cuddle or caress, or even woo? Are we so arrogant enough to believe that the love we feel for anyone is truly transcendent, and not mere technology? And also, is humanity any loftier than just a carrier for the trillions of bacteria that inhabit us? What suckers we are, that we behave as if we’re the rulers of the universe?

Okay, excuse the digression, your life has meaning. Happy now? Get back to watching the cricket, but do think about how it makes you feel, and the purpose of it all.