And Vijay Says…

It’s tax season now and I owe a bunch of documents to my CPA to file my taxes . It’s a pain in the neck to compile all of them . I do all my banking with one single company – and have multiple accounts with them . I can get a view of how much money is in all my accounts on the opening screen . But if I need tax documents – I need to go into each account and download them . There is no way to do a batch download or batch transfer to a cloud service .

It’s no different for mortgages and insurance policies and W2s and what not . I still have to go one at a time to each account to get the documents and manually compile it . Then my CPA has to look at each and put data into his software and file taxes. I am sure if this process were easier – I wouldn’t have to pay him a lot in fees , and he will make even more money than he makes today by having more clients.

I have gone through this problem when applying for mortgage as well – find documents one at a time, download it and then send it to the lender who looks at each PDF , and types the information to some screen and then someone takes a decision .

A (smaller) version of this problem happens when you join a new employer or start a side business.

There are 250 million or so tax filers in US . I would think there are at least 50 million mortgage applications each year as well . And each of them have to go through this time consuming and highly error prone process. Just thinking about it makes me want to scream !

What is funny (and sad) here is that vast majority of the companies – banks , mortgage lenders and the like – have some kind of customer 360 view for everyone they do business with . That is how they sell more and (hopefully) better service their customers . But these same companies, when they design their customer facing solutions, limit the customer to – at best – a dashboard that shows the combined view of accounts . It’s not done in a way that the customer can share information easily with the government , or a lender .

This situation is more than ripe for significant disruption . I would gladly pay for a service that can aggregate assorted documents for me as a secure cloud service – statements, tax forms etc – from the vendors I have accounts with . And then I should be able to just select the view I want to share securely with whoever I want – like the government , or a lender or my employer . These documents are all structured in a simple way – so it doesn’t even need to be shared in PDFs . An API based solution should be totally possible to provision .

Some combination of a company like Box and a company like DocuSign can solve most of this problem with existing technology and ecosystem . Tech is not the issue here at all – it can be solved by a range of tech from good old XML to the coolest blockchain and AI tech 🙂

Does anyone know if such a company exists today ? If not – I am seriously tempted to start one , or put some investment if someone wants to do it .

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 🙂