And Vijay Says…

Yumi, the young flight attendant in Qatar Airways flight from Doha to Chicago, is the closest I have acknowledged anyone to be similar to both my late grand mothers ! I didn’t tell her that though since I was not sure she will take it as a compliment 🙂

I was practically raised by my paternal grandma, Vijayalakshmi. She passed away when I was ten. The only other person I remember as fondly is my maternal grandma, Sankari . My own name – Vijayasankar – is a combo of both their names !

Growing up – the best part of my life was visiting grandma . And the part I enjoyed the least was going back to my engineering college dorm every Monday after spending the weekend at home. I knew I had to do it and never really fought it – but I couldn’t wait to get out of college and never do this weekly commute again . I had to clue the universe would just replace train and bus rides with plane rides !

A week ago, I had to do a last minute trip to India with my client. I took a combo of American Airlines and British Airlines to get there. I landed at 7AM in Bangalore airport and by 10AM I was in the first meeting of the day at the IBM office. Now, on the way back it’s Qatar Airways to Chicago and then American to Phoenix . I am typing this from the Qatar flight with about an hour left to land in ORD. And my mind is racing back to 1992 to the dread of catching Parasuram Express to Kollam every Monday morning from TRIVANDRUM central station.

While I had no bad experience on my way to India, I have not a single memory of what happened in the American and BA flights. I don’t remember the staff , or food or anything. It was a workhorse experience – totally efficient, and yet not memorable in the least . I wanted that flight to land early. And I can’t believe I am saying this – I really don’t mind that this Qatar flight that will land 30 minutes late will put my connection to Phoenix at risk.

I don’t drink alcohol on flights and I don’t like plane food all that much. But Yumi and her colleagues convinced me in the friendliest way possible to try their assorted non alcoholic drinks . Her supervisor who is apparently a foodie herself gave me quite a lot of insight on how they choose dishes to serve, how they take time to learn customer names and how to pronounce them correctly before they see us.

The bar for customer experience is the last great experience one has had . And having enjoyed the over the top service in the hotels in Bangalore and Delhi – it would have been impossible to go over that high bar . And yet that’s precisely what happened . The Qatar staff didn’t overwhelm me with attention like the hotel staff – they had a balanced approach of being there when I needed their attention , but leaving me alone for most of the time.

I also witnessed a teaching moment earlier in the flight. A fellow passenger asked for a cup of sparkling water and unfortunately they had run out of bottles . That is partly because of me – I must have had half their supply in the last 15 hours 🙂 . The young flight attendant seemed to panic when she got the request .

I saw the supervisor who was about 10 feet away calmly walk up to the customer , apologize and offer another beverage and then slipped a cookie from her pocket to the older gentleman . From his face I knew he was happy ! Her supervisor who saw me watching quietly told me “She will learn soon that the trick to thriving in this job is to ALWAYS stay calm . When you are calm, you will always find a quick solution”. I nodded in agreement – this is obviously true in my line of work too 🙂

I take something like 120 flights on average every year for work – and have been doing it for 20 years or so . After the first million miles – I completely stopped looking forward to getting into a plane . I try really hard to not fly for vacation – I would rather drive a car for 12 hours a day instead . Which is ironic, given my big goal while in college was to get a job that lets me get into a plane and travel the world frequently 🙂

Thanks Yumi, Leizel and the Qatar team for reminding me of the joys of flying – and for reminding me of my dear Ammoomma in the best possible way. And how I wish the other airlines sent their executives and staff to check out how you do a world class job and learn from you ! I absolutely look forward to enjoying your hospitality the next time .

One of the best books I have read in my childhood is Panchatantra . The way it’s structured, the first story ends with one of its characters saying “let me tell you a story” and leads on to the second story and then it perpetuates like that till the end . I have a feeling my post on automation might end up as a micro-panchatantra 🙂

Yesterday morning in Delhi, I wrote about a fascinating conversation I had with a Banker about automation and the potential for associated job losses . A friend of mine who read that post pointed out to me that her fear was that unethical computing practices might make job losses happen faster for women than for men .

She is an IT expert herself . And while she is not a data scientist herself , she understands how machine learning etc work and how it can figure out patterns from data it has access to . Her precise point is that if the machine is fed past data – wouldn’t there be a high chance that the machine will learn to be as bad or worse than the people who discriminated against women in the past ? And then won’t it just make that bias happen at scale since software can be distributed globally quite easily ?

It’s a VERY fair question and something that has been asked by many others before her. Bias is a real problem in data science – be it in the source data or in the model . Both data and the humans working on creating the model can perpetuate the bias.

Ethical AI is a topic very close to my heart and I have written and spoken about it several times .

Without making it too complex or technical – there are ways to identify such bias in both data and models . And once identified , it can be countered . While I agree that it’s a big problem and will take a lot of effort in creating awareness and implementing in actual projects – it’s at least possible to mitigate .

But that might not be the kind of bias we need to worry about most when a lot of decision making gets automated . Bias against a category – like gender, residential zip code etc – can be identified and countered with some effort .

But what if the algorithm goes against hundreds of parameters and each (or some combination ) contributes a little bit to the final decision ? This is the more common scenario of scoring – like a credit score calculation that looks at timely repayments, balances , history , number of accounts held etc and then comes up with one number at the end .

Credit scores only look at limited parameters and it tells you the handful of reasons why your score is low . But in a job scenario – it could be the photo of you with a hunting gun in your twitter profile , some image on your T-shirt on your Instagram account , the words you use on your CV and LinkedIn profile and a million other things which individually don’t look bad but collectively may make an algorithm figure out that you are not a great hire . And it might be really complex for a human hiring manager to explain to a candidate why she won’t be hired since it’s hard to understand the inner workings of such an algorithm .

This problem too has some possible solutions – which again needs significant work to make sure they are put into practice . For example a company can have a policy that if AI is going to automate a business decision – it’s mandatory that it is explainable . For example a neural network that comes up with a result should be able to be represented as a simple decision tree that a human can read and make sense . And just like test coverage and security checks are mandatory for code to be pushed into production – CI/CD pipelines have ethical gates too before a model gets to production .

Now about the scale question. All computing has that issue – both good and bad gets amplified significantly ! The way I look at it – even if Bias gets perpetuated at scale , once it’s solved – the solution also gets perpetuated at scale . And unlike humans who don’t all have the same moral and ethical compass – AI can have unwavering standards in each replica once it’s told what those standards are. Now – whether we can define the standards of ethics is a hard question in itself . My current thinking is that we cannot do that . And consequently – we will leave some decision making to humans to define the standards on a case by case basis and hence bring back the very problems we are trying to solve !

Automated decision making has a potential long term problem that we may already be seeing a bit of today, which has nothing to do with ethics – I think it makes us humans a little less sharp .

If my phone runs out of battery , I am sure I can find my way to my destination via a paper map or by asking for directions or by finding out which way is east or something . That is because I was already driving a long time before phones started having a GPS app . But I doubt my young daughter – who will start driving in a couple of years – can do the same if her phone ran out of charge when she is on her way some place. I doubt she knows of paper maps or even that AAA exists 🙂 .

This is not a new problem . My dad routinely used to make 500 mile plus trips without a map with our family and none of us ever remember him not making the destination in time . I don’t have that ability in the least .

PS : Let’s see if someone else inspires a follow up on this . Yesterday I wrote that post while in a cab . Today I am writing from my plane ride from Delhi . If there is a sequel, I hope it’s while I am static somewhere 🙂

I am in India for a week – spending time with my client and my team in Bangalore and Delhi . I had coffee earlier today with someone I met at the hotel lobby while waiting for my cab to pick me up – he is a senior banker in the public sector , and is apparently quite savvy on technology . Both his children are in US and in IT field, and he has visited a few times and is familiar with the US political scene and all that . He provided a perspective on automation that definitely gave me some food for thought . I am typing this from my cab ride on the way to my office .

India generally has a heavy leaning to socialist principles and labor is valued more than capital by the society . So the prospect of job loss – real or otherwise – gets people worked up very quickly . He saw that first hand when IT started automating some invoice processing type work at the bank. But the clerks were not fired (my guess is that it is thanks to strong labor unions) – instead they were trained to handle exceptions and they took more responsibilities at the bank .

Apparently that has worked out well – and he was surprised to see resistance to automation decrease rapidly when mind numbing repetition was eliminated from their day job. But he is convinced that the moment the first employee loses his or her job to computers – everyone will be up in arms . He thinks in a country like India with a lot of potential to expand business – one more generation at least will not face the risk of massive job losses . In his projection – based on size of population – India has another 30 years to prepare for it .

I asked him what he thought of more senior roles in management like his own job . He surprised me quite a bit with his reply – he said he expects most of those roles will just go away because there won’t be anything to do for majority of bank managers ! I pressed him for details

He thinks most of the managers just have incremental value add responsibilities today. They resolve conflicts with unions and customers , they make incremental changes to process , they interface with state authorities and they do a lot of reporting . Very few of them – his estimate is less than 10% – worry about things far into future . He is fairly convinced that as computers standardize processes and do it at great speed and accuracy – there won’t be as many conflicts to resolve , no reason to tweak process manually and not much reporting to do . So what would managers do ? He thinks banks will just eliminate those roles over time .

I asked him if he worried if that will happen before his retirement . He said “You haven’t lived here in a while or else you wouldn’t have asked this question . All these things will take twice as long as I estimate – or perhaps will never happen . Our government will have no incentive to let it happen and solve massive social upheavals nationwide”.

I nodded – I totally agreed he is right about his conclusion .

He said there is one trend that might force the government’s hand to allow more automation to happen after all . That is – if the consumers automate how they bank more and more ! Consumers already hate the friction of going to a bank (apparently no different from USA) and want a lot standard functionality in phones and web . And when most consumers behave that way the rest of the bank operations will be forced to respond to a similar way of functioning .

I asked him if he thinks computers can effectively function as equivalents to bankers if I have a problem to resolve . He said “You guys are the exception to the rule . NRI types will always have personalized attention from banks – you are special. We won’t risk computers messing up and you taking your business away from us. With you – our human bankers will just use computers on our desk to get you what you need faster. We can afford to treat you as special because we will save cost everywhere else with computers !”.

I couldn’t help but think he could really have my job – I have made this pitch countless times when explaining virtual agents and agent assists to my clients 🙂 . He just didn’t use fancy jargon – and his conviction was powerful !

I would have loved to continue the conversation for longer but alas my cabbie called that he has arrived . So I took my leave . As we shook hands he said “Vijay – just so I am transparent , I think for you NRIs to get personalized service from us when everyone else is talking to a computer – you maybe charged a little something extra”.

I told him “Sir, this last sentence is why I don’t think you will never get replaced by a machine” 🙂