Could you be replaced by an AI robot?

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It’s a Monday morning and you receive an urgent email from a client. They’ve received a letter from HMRC saying their company accounts are late and threatening a huge fine.

After a quick check you see everything was filed on time, so you ask for a copy of the letter. The client sends through a photo taken from a mobile phone and, as you suspect, it’s a reminder from Companies House that the Confirmation Statement is due.

This is a fairly typical problem faced by accountants, with clients giving incomplete, jumbled information using a mixture of spoken word, writing and pictures. It may be annoying, but at least it means you can never be replaced by a robot.

Or could you?

Artificial Intelligence (AI) is currently one of the hottest areas in technology and aims to do all the things you just did to help your client. So what exactly is AI, and how will it affect the accountancy profession in the future?

It’s all about cats

If you ever attend a conference on AI, it’s only a matter of time before someone mentions cats. The reason is humans can instantly recognise a cat, regardless of colour, breed or the angle it’s viewed from. Computers are good at many things, but spotting cats isn’t one of them.

To give computers this key skill, scientists looked at how the human brain processes and understands images. The information is translated into data and passes through various layers of neurons, with each layer taking the results of the previous layer and processing it further before passing it on to the next. Once finished, the brain can match the shapes pulled from the image to objects it recognises from the past.

Techies replicate this process using multi-layered mathematical models (or artificial neural networks), with several layers of nodes each performing small calculations. They then feed a few thousand images into the model, already knowing which of those images contain a cat. They use statistical techniques to set the model’s weights and parameters to make the model as reliable at spotting cats as possible.

More test data can then be fed into the multi-layered (or “deep”) model to see how well it works. The computer scientists check the results and recalculate the weights to make the model work better. This is the concept of “deep learning”.

Artificial neural networks and deep learning are two key elements of AI, as they mimic the analytical process of the brain and, like us, can learn from experience.

Speaking the lingo

So computers can think like humans. But can they speak like us?

Analysing human speech must be every scientist’s worst nightmare. We structure sentences in different ways (often with misspellings and bad grammar) and use slang, abbreviations, sarcasm and words with ambiguous meaning. We’ve been talking to people all our lives, yet there are still occasions when we misunderstand what others are trying to say.

Natural Language Processing (NLP) tries to extract information and meaning from speech, based not only on the meaning of words but also where they fall in the sentence and the words surrounding them. The rise of computing and the Internet has made this process easier, as we have access to large samples of real-life sentences (an example of “big data”) that can be loaded into a database and analysed.

NLP now works well. In a recent test at Stanford University, an AI model was given extracts from Wikipedia and asked questions on the content (e.g. “what is the capital of Kenya?”). The AI model scored higher marks than humans given the same test.

So how can AI technology help your client?

The theory sounds good, but how could AI technology be used to understand and respond to your client’s confused query?

Let’s run the initial email through a real-life NLP program. In my test, the program pulled out “letter” as the most important keyword, followed by “company accounts”, “HMRC” and “fine”. It recognised “fine” to mean a financial penalty rather than as a positive description (e.g. “fine weather”).

So this would give your AI software a starting point. Just like humans, it can then decide what to do based on its training and experience. This would consist of some pre-set rules and training data initially loaded into the software (for example, an accountancy firm’s email history of past queries and responses) plus any emails the AI software had processed since its initial training.

It may first spot the word “fine” and, based on a rule, check whether anything is overdue or was filed late. When the answer is no, it may search for previous emails with the same keywords and find that responses typically requested a copy of the letter. It could then construct a simple email and send it to the client.

Once a copy of the letter is received, the software can use an artificial neural network to analyse the image and spot the text. It runs the extracted content through an NLP program to determine the main keywords, and again checks them against its database. It concludes it’s a reminder to file a Confirmation Statement.

Are you scheduled for obsolescence?

Will the advance of AI technology mean the world no longer needs accountants?

Some implementations of AI technology are starting to be rolled out (and make a positive impact) in areas such as healthcare. But the good news is we are not yet at a point where AI software can think, make decisions and communicate with clients without them even realising they’re speaking to a computer - the Holy Grail of AI developers.

That said, never before have we had such huge amounts of cheap computing power, storage, bandwidth and test data available. The tech titans of the US and China are working hard to lead the field, and investors are falling over each other to pour money into AI startups.

Over the next five or ten years, AI technology will continue to develop quickly and will ultimately spread into areas such as accountancy. So don’t be too surprised if, one far off day, the annoying AI robot from HR hands you a P45.

About Matt Bailey


Founder of Aegia Cloud Systems (Gbooks), the leading cloud-based tax and accounts system.


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23rd Jan 2018 17:23

Well, I do think that some of the blogs on here have been written by AI robots.

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By Matrix
24th Jan 2018 22:24

Can my clients be replaced by robots though? After about 5 emails and 3 months and talking my client through how to find out his bank interest figure, a robot sounds desirable.

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25th Jan 2018 11:28

"Danger! Danger!" - waves arms.

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25th Jan 2018 11:56

Matt, hi.
All this sounds good/bad depending on one's viewpoint.

The AI 'learning' aspect is fascinating. Machines neither 'think' nor 'learn' (not yet, anyway) so instead currently rely on their programming to decide the action to take. They will need lots of information and experiences and indeed coding to enable a choice of actions. There are huge practical problems that will have to be overcome. And we shouldn't overlook that an accountant or other service provider may have a liability to their clients if they give incorrect advice.
The robot you've outligned is surely no more than a bot that will sift queries / messages and deal with those which are 'simple' (eg ask for more information) or refer the matter for resolution by a higher intellect (the accountant?).

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25th Jan 2018 17:15

Hi Mike, traditional computer programming relied on the programmer telling the computer what to do in every possible scenario. If the user wanted to do something new the programmer would need to add it to their code, test it, debug etc.

AI technology is more about setting up a framework so the software can see, hear or read information in a similar way to us, and then find the best course of action based on information in an ever-increasing database.

There may be times when the software doesn't know what to do and has to prompt a human to take over or answer a query. But it can then add the response to its knowledge bank (without the need for any fresh programming) and can refer to this memory again in the future.

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25th Jan 2018 18:20

AI - the computer - will require programming, even if it is to evaluate information/data and make a decision.

The range of responses/action the AI could take may have to be determined/restricted (eg insufficient data to identify a course of action other than refer the decision/action to a human).

AI has to 'learn', which may be achieved by trial and error - but that requires huge amounts of experiences / data and 'feedback' (ie was the response /action correct - indeed, what is 'correct'?).

Trial and error. Did the AI operating the Tesla car that caused a collision and the death of the human 'driver' last year 'learn' from its mistake? If so, how? Has Tesla re-programmed the AI?

AI offers significant opportunities to improve so many things, but we should be aware of its limitations.

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26th Jan 2018 15:35

Too late.
HMRC already thinks software can replace accountants.
PTA's and MTD are just simple examples.
And if not, HMRC will just ignore accountants.

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28th Jan 2018 13:13

Well, I suspect at this time of year I really should be replaced by Marvin, we both at the moment display similar GPPs .

However come Thursday Marvin would not be appropriate which suggests one will need to be able to set the GPP according to mood, this had advantages if one will say be able to have a Terminator setting included in the options.

At least I will have hung up my calculator when it all comes to pass,

“Sorry, did I say something wrong? Pardon me for breathing, which I never do anyway so I don't know why I bother to say it, oh God I'm so depressed"

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29th Jan 2018 14:55

As always, it depends on what you mean by "accountants" and on your timescale. My views ... Bookkeeping has been going for years, but not yet entirely gone. Accounting in terms of record keeping, preparation of basic financial statements and tax compliance is/will be going shortly. The more complex tax advice will eventually go as AI bites as the interpretation of complex IFRS accounting standards and judgement calls on areas such as valuations, provisions, etc but that is further off. Many of the advisory and interpretive roles of public accountants will take even long, if ever, to fall to AI and the same applies to those functions that finance directors carry out.

The need for auditors (in a general usage of this word) to check on the quality of input and the reliability of output will probably increase.

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