AI and the CPA: OpenAI's ChatGPT will Blow Your Mind! Try it Now!

We previously discussed OpenAI in this post. In that post, I closed with this comment:

"We should be aware of the concept of exponential change. Technology, like AI, improves at an exponential rate and not a linear rate. Consequently, monitoring the space is key for CPAs and other to ensure that they see change coming and adapt accordingly."

And so, my fellow CPAs, you need to check out how much AI has advance in the two years since that post. It's absolutely amazing to see how advanced the technology is and how quickly it has come:

YouTube is one thing. But testing it out is another. To be honest, I was about to review the video and then summarize it. Then I thought, why not ask ChatGPT? 

Question to ChatGPT: "What are 5 key takeaways for CPAs with respect to ChatGPT?"

Answer: 

1. ChatGPT is a large language model trained by OpenAI.
2. ChatGPT has a knowledge cutoff of 2021, and it does not have access to the internet or current events.
3. ChatGPT is able to generate human-like responses to a wide range of questions, but it is important to keep in mind that it is a machine and may not always provide accurate or complete information.
4. ChatGPT is not a substitute for professional advice or guidance, and it should not be used as the sole basis for making important decisions.
5. ChatGPT is intended for general informational purposes only, and it is not a substitute for professional judgment or expertise. It is important for CPAs to consult with appropriate sources and to exercise their professional judgment when making decisions.

Reading through the takeaways, it seems like it added an extra dash of risk management. Could it have accounted for our risk-aversion?

Then I thought, why not ask it directly about the video itself? 

Question to ChatGPT: "What are 5 key takeaways from It’s Time to Pay Attention to A.I. (ChatGPT and Beyond)"

Answer:

1. Artificial intelligence (AI) is a rapidly developing field with the potential to significantly impact many aspects of society, including the accounting profession.
2. AI technologies, such as chatbots and language models like ChatGPT, are becoming increasingly sophisticated and can be used for a wide range of applications.
3. It is important for CPAs to stay informed about the latest developments in AI and to consider how these technologies may impact their profession and their clients.
4. While AI has the potential to improve efficiency and accuracy, it is important to carefully consider the risks and limitations of these technologies, including the potential for errors or biases.
5. CPAs should consider ways to incorporate AI into their practices, such as by using AI tools to automate certain tasks or by providing guidance to clients on the use of AI. However, they should also ensure that they have the necessary skills and knowledge to effectively use and understand these technologies.

Notice how I did not have to tailor this questions for CPAs? ChatGPT automatically brought the context over from the previous question.  (As for how good this summary is, you can judge for yourself.)

Then, I decided to ask it about how exponential technologies will impact the CPA profession. 

First question, "Will blockchain replace the need for financial auditors?"

Answer:

"Blockchain technology has the potential to revolutionize many aspects of the financial industry, including auditing. However, it is unlikely that blockchain will completely replace the need for financial auditors.

One of the main features of blockchain is its ability to provide a tamper-evident record of transactions. This can be beneficial for auditing purposes, as it allows auditors to more easily verify the accuracy and completeness of financial records. However, auditors still need to be able to interpret and analyze the data contained in these records, and to ensure that the data is consistent with other information and documentation.

Additionally, while blockchain can provide a secure and reliable record of transactions, it is not a substitute for the expertise and judgment of trained financial professionals. Auditors bring a deep understanding of financial principles and practices, as well as the ability to identify and assess risks and potential areas of concern.

Overall, it is likely that blockchain will augment and enhance the role of financial auditors, rather than replacing them entirely."

Notice the nuanced response? It should have spoke to validity, instead of completeness when it came to how the blockchain will assist the auditor. However, it didn't just list all the audit objectives just "to be safe". 

Then I asked about artificial intelligence:

Question: "How can AI be used to automate financial auditing?"

Answer:

"Artificial intelligence (AI) can be used to automate certain aspects of financial auditing, such as the analysis and interpretation of financial data. This can potentially improve the efficiency and accuracy of the audit process.

For example, AI algorithms can be trained to analyze large amounts of financial data and identify patterns and trends that may not be immediately apparent to human auditors. This can help auditors to more quickly and effectively identify areas of potential risk or concern.

AI can also be used to automate the testing of transactions and the evaluation of internal controls. For example, an AI system could be trained to perform automated tests on transactions to ensure that they are recorded correctly in the financial records. This can help to reduce the time and resources needed to perform these tasks manually.

Overall, the use of AI in financial auditing can help to improve the efficiency and accuracy of the audit process, while also freeing up auditors to focus on more complex and higher-level tasks that require human judgment and expertise."

Recognize the theme of "race with the machine" in both this response and the previous blockchain response? This is especially integrated into the last paragraph, which speaks to what AI can do versus what "human judgment and expertise" can do. Also, notice how it explains AI role in both risk assessment and testing of internal controls. That is, it had enough where "understanding" to breakdown the response into different aspects of the audit. 

When looking at this, we need to ask ourselves: is this inflection point for exponential rise of AI? 

Do review the last part of the video, where Samuel H. Altman, CEO of OpenAI, explains how he anticipates the impact of such technology on the legal profession. (The video earlier takes about how Josh Browder's Do Not Pay, will leverage the tech. I had previously seen Browder on a panel in 2016; see this post for the video). 

It's not quite a stretch to apply what he says to the CPA profession. There are key differences; in that we opine on financial statements, provide tax advice based on financial data, and the like. However, audit data analytics tech has been around for decades. It's just a matter of getting the different parts to talk to each other. 

Clearly, it's early days for ChatGPT and many issues need to be sorted out. For example, it has already earned the moniker "CheatGPT" for how it can be potentially used as a short-cut by students. That being said, it's clearly the biggest watershed moment for AI and the white-collar workforce, since IBM's Watson defeated Ken Jennings and Brad Rutter. 

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else

AI and the CPA: What should CPAs know about GPT3?

In the epic battle between man versus machine, the chess champion Gary Kasparov threw the match because it is alleged that he thought that the AI-powered system did a well-calculated move. In reality, it was just a random move that the system threw out because it had experienced a technical glitch.

One up-and-coming AI-enabled service to watch is GPT-3 from an organization called OpenAI. OpenAI was started by Elon Musk. It’s in beta right now and in a really raw state but the capabilities that have surfaced are pretty amazing. 

One capability (as noted in the video) it has is summarizing long reads. However, there are serious flaws that need to be worked out. For example, it advised a fake patient suffering from depression to kill themselves. So it's not going to be rolled out at a hospital any time soon, but it is something definitely watch.

AI and CPAs: Competitors or Collaborators?

AI could make the profession more sustainable, as these mundane tasks could be handed to a system. MIT’s Eric Brynjolfsson describes this concept as "race with the machine". The idea is that doctors, accountants, lawyers, can work better together with technology. It’s almost like a second set of eyes or someone that can help you assess whether the professional judgement on an issue is correct.

However, this is not something that is currently on the horizon. 

What’s more realistic is understanding where the economics of automation will apply for more basic things like have a more timely close. McKinsey put out a study in August 2020 that found automating and increasing the accuracy of forecasts helped management make better decisions. One case study they highlighted was a manufacturer that was able to reduce inventories and product obsolescence by 20 to 40 percent. 

Change is coming faster than we expect

We should be aware of the concept of exponential change.  Technology, like AI, improves at an exponential rate and not a linear rate. Consequently, monitoring the space is key for CPAs and other to ensure that they see change coming and adapt accordingly. 

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else

Serendipity: Beyond the reach of Robot Professionals?

Came across a story about how Dr. Behfar Ehdaie at Memorial Sloan Kettering Cancer Center was figuring out how to deal with the emotions that come with a discovery of prostate cancer. His novel solution gives may give us some insights into the limits of robots in the professional world.

What he found was that his patients opted for radical treatments, such as surgery or chemotherapy, that resulted in side-effects that actually ended up being more harmful. To use a cliche, the cure was worse than the cancer.

For such patients, "the medical consensus is that active surveillance often is the appropriate treatment for small early tumors". Of course, such an approach is not risk-free, but the problem is that "despite the data showing that this approach is safe, about 50% of eligible men don’t get it either because they turn it down or their physicians don’t embrace it. Medical experts say many men have been overtreated, as their cancers probably posed little immediate danger."

What was his solution?

Negotiate with patients.

As noted in the WSJ article referenced above, he contacted Harvard professor Deepak Malhotra who had authored an article on the topic to develop strategies on negotiating with the patient. Leveraging lessons from behavioral economics was to make monitoring the anchor instead of surgery or chemo. Dr. Ehdaie and professor Malhotra devised a lecture that was delivered to doctors to help them learn from Dr. Ehdaie's successes with this approach.

But what does this have to do with limits of robot-professionals or robopros?

When it comes to cancer treatment and robots, one can't complete the conversation without mentioning IBM's Watson "Oncology Edition". In fact, IBM has a partnership with the same Memorial Sloan Kettering Cancer Center that Dr. Ehdaie works at. Here is a promo-video that speaks to the promise of Watson:

The key to understanding the limits to robot-professionals is the backstory on how Dr. Ehdaie first decided to explore negotiations a way to deal with the issue.

This is where serendipity comes to play.

He was exposed to such concepts with discussions with his wife who is an MBA. Meaning that he went beyond the cancer treatment journals and then discovered a non-standard approach to dealing with a problem. Robots are not good at this. Machine-learning and AI is only good as what you teach it. Even "simple" tasks require thousands of man-hours to train such algos. Perhaps this can be overcome, but currently, it is a real limitation of AI.

Does this make humans indispensable?

Really depends on the objectives that govern the profession and the organizations that hire them.

If it's about cost-cutting and making the process efficient and streamlined, robots are perfect creating a fossilized bureaucracy that is resistant to change. Think about how financial institutions have yet to overhaul their ancient banking systems coded in COBOL:

"In the United States, the financial sector, major corporations, and parts of the federal government still largely rely on it because it underpins powerful systems that were built in the 70s or 80s and never fully replaced."

Similarly, if Dr. Watson replaces a large component of the diagnostic process it would become hard to dislodge it from the cancer treatment process.

On the other hand, if organizations recognize the value of human beings in being important to overall objectives of the profession - patient care, audit quality, etc. - then human judgment must be hardwired into the organization's DNA to avoid the development of such an inflexible system.

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else

AI and the Audit: What does a robot need to audit your numbers?

In the previous post, we examined the value propositions that Appzen's AI brings to auditing expense reports.

In this post, we analyze what insights we can extract from Appzen when it comes more broadly to applying AI to the external financial audit.

The following gives a refresher on how the Appzen AI audit works:

Based on this we look at a number of factors that exist in this process to develop

Standardized process:
The expense report process that has been fairly standardized for over a decade: employees submit a digitized report of what they spent, expense codes, commentary and all the supporting documentation (e.g. receipts, invoices, etc.).  This is similar to how factories needed an assembly line before they could be automated.

Standardized capture and presentation of audit evidence:
I think this is a key piece: the actual audit evidence (i.e. receipts) must also be included in what's submitted to the auditor. As the evidence is provided in a standardized format, it enables machines to analyze these digitized source documents to run the necessary correlative models to run the risk scores and enables the automated analysis.

Audit evidence retains its chain of custody through the digitization process:
The auditor does not need to expend additional resources verifying that the evidence actually relates to the item being audited, nor do they have to expend additional resources ensuring that the independence of the evidence wasn't lost through digitization process. For example, when receiving a bank confirmation the auditor needs to ensure that this received directly from the bank and not the client.

Evidence provider identity is verified and contractually obligated to follow-up with the auditor:
The party submitting the audit evidence, the employee, has been verified in the system through the employee onboarding process. The implication of this is that the auditor doesn't have to expend audit resources confirming the identity of the evidence provider. Secondly, and perhaps more importantly, the auditor doesn't have to expend significant resources following up with the evidence provider. For example, not all customers will respond to accounts receivable confirms and then auditor will have to perform alternate procedures.

Evidence provider has incentives to produce the proper evidence: 
The previous point is closely related to the issue of incentives: if the employee fails to provide evidence then they will not be reimbursed. This puts a strong incentive on the employee to provide the evidence in a timely manner.

Provider of the evidence is trained on providing evidence:
The employee has been trained to provide complete, accurate and valid evidence. They also have access to help if they have issues with submitting expense receipts or understanding whether that evidence will be accepted.

Violations can be clearly defined and examples of violations can be taught to the system:
For fraud or errors to be flagged there needs to be rules that can be fed into the system to identify whether the item submitted needs further review or audit. For example, if the amount on the receipt doesn't match this would be flagged and has a high likelihood of error. But more importantly,  the examples of violations identified can be fed into the system to teach the system (via machine learning) what to look for.

In a future post, we will use these factors to look at how easily (or not) AI can automate financial audits.

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else

AI and the Audit: Why hire a Robot as your Auditor?

On this blog, we've covered the topic of exponential change and how audit/accounting is prone to such forces.

Despite this, I am tempted to say financial auditing is different. It's not like factory work or more controversially like the pharmacist profession where AI claims to offer a safer alternative to dispensing medication.

But does that make me just one of the people who think that their profession is unique because they are in the midst of seismic change but refuse to see the writing on the wall?

At the same time, I don't want to come across as an alarmist claiming that the world is going to end when it really isn't.

It's the challenge of nuance.

While trying to figure out how to tackle this challenge, I came across AppZen; an app that uses artificial intelligence to audit expense report. It was identified in this post as being one of the game-changers in the fintech scene and was also featured in Accounting Today.

According to the company's website, the application "combines computer vision, deep learning, and natural language processing to understand the full context of expenses, not just amounts, dates, and merchant names. ReceiptIQ detects unauthorized charges in real-time from receipt images, boarding passes, travel documents, cell phone bills and any other expense documentation. Cross-checks expenses in real-time against thousands of external and social sources to determine if they are legitimate and accurate... Real-time identification of unauthorized upgrades in airlines, hotels and car rentals as well as out of policy claims for hotel laundry, alcohol purchases, cell phone charges and more."

Reviewing the company's video, I was able to extract the following value propositions:

• "100% Testing":  I put it in quotes on purpose because the idea is that the whole population is analyzed but only the high-risk ones are further analyzed. That is, this is still "examining on a test basis" but uses a risk based approach to identify what reports should be further examined. This is in contrast to the manual approach of sampling.  
• Automated exception analysis: Closely connected to the previous point, but to emphasize that there is an automated review of the population.
• Real-time analysis: Reports can be analyzed instantaneously. Although not explicitly identified in the video, this could have real world savings. Faster reviews - leading to faster reimbursement to employees - could reduce the overall amount owing on corporate credit cards thereby offering more favourable position with the credit card companies. 
• Seamless integration into existing processes: Add-on to an existing process is a much easier sell than an app that requires replacing the existing app you may have just bought.  
• Use of external data: The app uses 100s of external data sources to develop. It seems that this assists in building an expectation of whether the expense needs further analysis. 
• Limited false positives: Not explicitly stated, but it is strongly implied that the number of reports that need to be reviewed is few - meaning it's not flagging reports that are valid.   
• Reduction of audit costs and fraud: Finally, the app promises greater efficiency in the use of audit resources deployed and greater effectiveness in catching fraud. 

When looking at these benefits of AI-enabled automation, they are based on certain assumptions that may exist in the expense report realm but not in the external audit realm. For example, accounting records at a company are not normally accompanied by a digitized copy of the source document (e.g. invoice, receipt, etc.) that provides evidence of its validity, accuracy, etc. of that accounting entry. 

So which of these assumptions applies in the world of external financial audits? 

This will be the topic of the next post where I will develop a list of factors that enabled expense report to by automated by AI and see if they apply to our world. 

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else

RPA and the Accountant: A path out of the mundane?

One of the latest hype technologies is Robot Process Automation (RPA).

My first question when coming across this, is what is the difference between this and cognitive computing? 

As can be seen by these videos, it's more about "dumb" automation instead of "smart" innovation: where routine tasks are handled by the system instead of a person. This is in contrast to something like IBM's Watson, which attempts to understand language and offer probabilistic judgments as to what is the right answer to a question like it did on Jeopardy!


The first video (produced by Deloitte UK) does a great job of actually showing us how RPA can automate the process of extracting information/documents from email and the generating invoices through the company's ERP:

The strength of this video (produced by EY) is showing us the business case for RPA:

The idea is that RPA can automate routine tasks, instead of offshoring. In other words, it brings the world of automation onced reserved for the assembly line to the back office.

As described in this Deloitte publication, it puts RPA as the first step towards a cognitive enterprise - automate the task and then bring cognitive, AI, machine learning, etc., into the process to make it smarter.

To use a maturity model approach, RPA is the first level in bringing together the necessary data and processes to actually train the algorithm to make it smarter.

What does this mean for auditors and accountants?

For accountants, the back office is going to require less people in terms of executing these mundane tasks.

However, this doesn't necessarily mean that jobs will be lost.

As with the advent of cloud computing, the enterprises will have to determine whether such talent can be used more effectively to improve the quality of financial reporting and work on the back log of finance projects that haven't been attended due to staff working on these low-value tasks. That being said, the problem of meeting quarterly targets to feed investors insatiable desire for profits is something that can't be ignored when discussing whether management will choose profits over better processes.

For auditors the story is a little different.

The reality of the profession is that it can't retain talent because people find the work unsustainable: it's hard to shutdown your personal life for a third of the year or more to meet the needs of clients during busy season.

RPA and automation could make the profession more sustainable, as these mundane tasks could be handed to a system instead of a junior. This is similar to the "race with the machine" concept I mentioned in this post, when referring how Watson is helping doctors treat cancer.  Auditor could then focus on more value added tasks, such as assessing aggregate risks, industry trends, etc. Such insights will improve audit quality and give clients better understanding of business and audit risks, making the work more interesting for both auditors and auditees alike.

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else.

AI-as-a-Screenplay Writer: Computer overlords strike again?

Normally when I discuss artificial intelligence on the impact of work, it's in the context of the automation of accounting and auditing work (A3W). However, a story that's been circulating for past few days in my Google alerts is the story of the movie Sunspring. Unlike most movies it's not written by human being, but rather it is written by a computer.

Ars Technica, who hosted the online debut of the movie, noted that the script was "authored by a recurrent neural network called long short-term memory, or LSTM for short. At least, that's what we'd call it. The AI named itself Benjamin."
The movie is really odd to put it nicely. However, it does comes across as one of those art movies that (also) don't make any sense. The song in the movie is also generated by the machine.

However, this is not the first time that algorithms have been trained to be artists. Chris Steiner in his book "Automate This: How Algorithms Came to Rule Our World" notes that Emmy,  an algorithm, "produced orchestral pieces so impressive that some music scholars failed to identify them as the work of a machine". In a piece he authored for the Wall Street Journal he notes "analyzing only the script, an algorithm from Epagogix, a risk-management firm that caters to the entertainment industry, predicts box office grosses. Epagogix broke into the business when a major studio allowed the firm to analyze script data for nine yet-to-be released films. In six of the nine cases, its predictions were spot-on. Algorithms have since become an essential tool in Hollywood."

If the chaotic world of creative works can be automated by algorithms, then I think the predictable, routine world of debits and credits can't be too far behind.

CATS2016: Exponential Tech & the CPA

Today, I presented at the Canadian Accounting Technology Show and discussed how exponential technologies and their potential impact on the profession.

During the presentation, I promised a blogpost for the attendees who wanted to dig deeper in the presentation. So here it is!

IBM Watson's Victory over Ken Jennings
During the talk I refer to Ken Jennings and Brad Rutter's defeat at the hands of IBM's Watson. (See Engadet's video for more on this "exponential event".)
This post gives some background on the new "space race" between the tech-giants for the killer AI app and also gives a link to Ken's talk.

For additional information on Watson and the medical profession check out this video.

Exponential versus Linear Technological Change
Kodak - who invented the digital camera in 1975 - was ultimately disrupted by that very same technology. In fact, one of their employees applied Moore's Law to pixel's per dollar in digital cameras.

Why?

The problem illustrate that Kodak (as well as Polaroid) had linear thinking and didn't realize how quick digital technology would become the norm and preferred way of consuming photography. In this post, Peter Diamandis talks about how 30 exponential steps contrasts to 30 exponential steps (and talks more broadly about linear vs exponential thinking) and Ray Kurzweil talks about the infamous story of how the inventor of chess requested an exponential amount of rice (and is rumoured to have lost his head).

Predictions on the Automation of White Collar Work:
These stats are what actually prompted me to propose to CPA Canada that we should have a talk that would discuss this phenomenon. The variety of sources that have chimed in on the topic - combined with the understanding of exponential change - highlights the importance of looking deeper into the trend instead of dismissing it as just fear, uncertainty and doubt (FUD). This of course is not just limited to the accounting profession, but impacts all white collar worker (check out IBM's Watson latest application to automate aspects of the legal profession

• "Job destruction will happen at a faster pace, with machine-driven job elimination overwhelming the market's ability to create valuable new ones.” (Gartner)
• “…knowledge work automaton tools and systems could take on tasks that would be equal to the output of 110 million to 140 million full-time equivalents (FTEs).”’ (McKinsey)
• ‘94% probability accounting/auditing will be automated’ (Oxford Study)
• Finance Department has seen a decrease from an average of 119 people (2004) to 71 people (2014); a reduction by 40% (Hackett Group; as taken from this WSJ article "The New Bookkeeper Is a Robot")

Exponential Technologies
As noted during the presentation, the key exponential technologies that are likely to enable the automation.

Artificial Intelligence: "Science of making computers do things that require intelligence when done by humans." During the presentation, I mention this pharmacist robot being able to dramatically reduce medications errors, which according to the FDA is responsible for 1.3 million injuries.

For other information check out this Deloitte publication on AI and Cognitive.

Internet of Things: "Billions of interconnected sensors and devices will soon exchange data; effectively the physical flow of goods, people, and things will now leave a “digital trail”." RFID inventory does provide some insights in how this digital exhaust left by physical goods can improve inventory management and responsiveness to customers (see this RFID Journal article for more details).

For more on IoT, check out the Deloitte TMT Prediction regarding the technology.

Blockchain: "The blockchain dis-intermediates the need for a centralized trusted authority to administer an exchange of value between parties." As I note in the presentation, I feel the blockchain needs a lot of nuance when discussing how the technology has the potential to disrupt the profession. The technology (as implemented in the exchange of the cryptocurrency Bitcoin) itself won't replace the audit because its controls are designed for the purposes of giving comfort to a retailer, such as Overstock.com, that the buyer has not spent the currency somewhere else. However, if a retailer was then to tell an auditor that they sold goods to these public addresses, the auditor would need to verify that the retailer was not selling the goods to itself (i.e. they would need to verify that the addresses that the retailer sold to are not controlled by the retailer). In other words a sale for the purposes of Bitcoin is not a sale for accounting purposes.

That being said, auditors can’t ignore blockchain as it is the first decentralized approach to exchange value that eliminates the need for a trusted intermediary.

To understand the blockchain better, check out the following videos:

• Blockchain technology will drastically change our lives: This video gives a good overview of the implications of bitcoin and illustrates the role of the network in maintaining the ledger.
• How Bitcoin works under the hood: There is a 5 minute non-tech video, 5 minute tech video and a 22 minute video, which all do a good job of using animation to explain how bitcoin is tamper-proof.
• Khan Academy: The videos are about 90 minutes in total, but it is comprehensive. 

Crowdsourcing: "Process of obtaining needed services, ideas, or content by soliciting contributions from a large group of people, and especially from an online community, rather than from traditional employees or suppliers."

For more on crowdsourcing, I wrote a post on the potential impact on crowdsourcing. The post gives a good background exploring the use-cases brought up by Jeff Howe (who coined the term crowdsourcing).

Near the end of the post, I noted that:

"Can accountants/auditors be crowdsourced like the way professional photographers were? It seems were crowdsourcing works best is an arena where you find hobbyists who do such things out of passion instead of obligation."

Since writing that post I found Gigwalk which illustrates how non-expert tasks within accounting or auditing can be done by the crowd (see this post near the bottom). Also, during the CATS conference it was noted that 50% of practitioners will be retiring over the next 5 to 10 years. Such retirees could form a huge pool of people who want to work casually in their retirement thereby enabling the audit to be crowdsourced.

Concluding thoughts
To meet the challenge of the exponential change, I feel that we need to do the following:

• Hands-on Approach to Technology: University courses on programming, data analytics and data sciences should become a standard part of the accounting student's education. Although tools change over time, I think accounting students who have an open-source statistical package like R would have more options in terms of employment. With respect to data science, (audit) sampling belongs to an era of small data. Consequently, for auditing theory to be keeping pace with the way big data is transforming the way organizations are dealing with their data auditors need to be able traverse data science and auditing theory. 
• Bring in the "hackers": An extension of the above recommendation, is to get the people who think outside the box and disrupt the way we do things.
• Greater focus on cyber security: According to Alec Ross, cyber security is currently a 400 billion dollar problem and is expected to be a $175 billion industry by 2020. Security is a natural extension for CPAs who already need to understand internal controls, governance and concepts of risk (impact, likelihood, threats, etc.). With IoT, the security risks can only be expected to grow exponentially as now even the IoT-enabled fridge can be hacked (and the FTC thinks so as well).
• Smart Contracts+AutoRepos of Smart Cars = Flash Crash¹⁰: As I have written previously about AlgoTrust (second post and first post), I noted that this was another area that CPAs can focus on - auditing algorithms. Just imagine how, these algorithms can feed into blockchain enabled smart contracts that could trigger a massive repossession of smart cars - leaving a city in chaos as people try to figure out how to get home. In other words, CPAs can act as independent monitors of algorithms to ensure such risks are safeguarded against. 
• CPAs-as-a-Crowd: CPAs should leverage the combined power of social and cognitive to get smarter by sharing knowledge and using "smart rooms" that use machine learning and other AI technologies. 

To brings such change the profession, will not the work of one entity alone. Firms, educators, professional bodies and companies need to work together to ensure that the CPA profession will thrive in the world of exponential change that is just around the corner. 

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist that is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else.

Artificial Intelligence: The new "space race" for the tech-giants?

When IBM's Watson defeated Ken Jennings and Brad Ritter on Jeopardy!, it was a shock. As Ken Jennings describes in this Ted Talk, he had no idea that a computer could possibly defeat him at Jeopardy! On this Ted Talk, Ken Jennings describes how he never thought that a computer could beat him:



And he's right.

How can a computer possibly understand that "feel can smell" and a "nose can run"? 

But on February 16th 2011, IBM's Watson did precisely that: it was able to defeat the two reigning human champions Ken Jennings and Brad Rutter. And with that IBM ignited the space race for artificial intelligence.

Although people may point to the wide array of personal digital assistants from Apple (Siri), Microsoft (Cortana) or Google Now as the true birth of the AI space race. However, these application are limited to the use of the personal arena. Anyone who used things like Google Now - which can link your calendar to traffic patterns and tell you if you'll be late for appointment - can tell how amazing it is to how have a digital assistant work behind the scenes to keep your day on track. That, however, is limited to the consumer realm. Where AI gets real interesting is the B2B realm: Watson has made some strides in automating the FAQ process. However, it's real promise has been demonstrated in the cancer treatment realm, where it enables doctors to "race with the machine" combining the millions of pages of medical journals and articles to determine the best cancer treatment for patients.  Watson is available in a cloud offering to developers who submit applications.

But IBM is not alone and so the AI Space Race is on!

As for the other vendors, see the following:

• Google's prediction API
• Amazon Machine Learning
• Microsoft's Azure Machine Learning

However, the one that I am really waiting to hear about is coming from the makers of the Siri, Viv.ai. They are hoping to build AI as a service, similar to Bluetooth, that will be embedded in all hardware. I will leave you with the following quote from the Wired article that discusses the possibilities of Viv.ai:

"Viv...generat[es] its own code on the fly, no programmers required. Take a complicated command like “Give me a flight to Dallas with a seat that Shaq could fit in.” Viv will parse the sentence and then it will perform its best trick: automatically generating a quick, efficient program to link third-party sources of information together—say, Kayak, SeatGuru, and the NBA media guide—so it can identify available flights with lots of legroom. And it can do all of this in a fraction of a second."

Time for Windows 10? I can't wait!

I have been overly optimistic about Windows in the past, but here me out!

Boy Genius published a post on the future Windows 10 that they are releasing next year. (Note Microsoft decided to skip Windows 9 altogether).

And does it looks good. As can be seen in this video, it will feature Cortana who is Microsoft's personal digital assistant that incorporates voice search, voice commands (i.e. you can get Cortana to set-up an appointment with you) and machine learning (i.e. it learns from your interactions.
Impressed?

It speaks to the overall move towards using natural language processing (NLP) and elements of Artificial Intelligence. Apple was arguably first to the scene with its Siri application. However, IBM's Watson is also a clearer example of where this technology is heading. Gartner refers to these types of technologies as "smart machines", which they claim has the following implications:

"Most business and thought leaders underestimate the potential of smart machines to take over millions of middle-class jobs in the coming decades," said Kenneth Brant, research director at Gartner. "Job destruction will happen at a faster pace, with machine-driven job elimination overwhelming the market's ability to create valuable new ones."

Will Cortana take your job? Well, let's just enjoy the possibility that Microsoft may build in some real cool NLP technology into your every-day computer and worry about that one a future post!