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THE IMPORTANCE OF CONTEXT IN PRACTICAL AI APPLICATIONS

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By looking at a typical AI application, Dr John Yardley, CEO, Threads Software, discusses how AI processes must take account of humans if they are going to replace them.

 

Almost every business is influenced by human sentiment. And despite its embrace of digitisation, the finance industry is no exception. Share prices, currency movements, investment choices are driven not just by economics but by human emotion and the processes the human brain uses to make decisions.  If we are going to replace humans with machines, we must not cherry-pick the bits of human thinking that we can most easily replicate.

The perception of Artificial Intelligence has changed somewhat since Alan Turing coined the term in the 1950s. Turing said if we cannot distinguish a machine’s behaviour from that of a human, then the machine can be said to be intelligent. Nowadays, we seem to be defining AI as computer programs that emulate the human brain rather than mimic human behaviour. Neural networks, for example, are frequently touted as the pinnacle of AI, but if the neural network in your self-driving car causes you to jump a red light,  we would not describe that as intelligent – no matter how sophisticated the algorithm. If the machine is not fooling the human, not only is it not doing the intended job, it could be negatively affecting the human’s view of it.

 

John Yardley

A practical example – Automatic Speech Recognition

Let’s take the application of ASR (or automatic speech recognition, often wrongly described as voice recognition). ASR can loosely be described as getting a computer to transcribe acoustic human speech into digital text. Few would argue that this is an AI task since what we are seeking to do is replace one of two humans involved in some dialogue. If this can be done without alerting the remaining human to the fact that he/she is talking to a machine, then for sure this would meet Alan Turing’s intelligence criteria and, more important, provide potentially enormous benefit.

However, while some parts of the human process for understanding speech can be emulated using ASR, we must accept that the human listener may be using far more information that we are giving the machine. In a physical conversation, humans will be exchanging gestures, looks and body language, not to mention prior familiarity with the topic of conversation, understanding the accent, and the words being used. Presenting a machine with only a pure acoustic conversation is depriving it of a large proportion of the information available to the human. Even in a telephone conversation, humans will have significantly more knowledge than machines.

Many would be surprised just how good computers are at recognising random words and how bad humans are at articulating meaningful sentences. I have shown people ASR transcriptions of their speech and been met with incredulity. Yet when listening to the recording, the speaker is often forced to admit that the computer generally gets far more correct than he or she would give it credit for.  What the speaker and listener forget is how much interpretation they were applying to filter out the “ahs” and “ums” and “rights” and the repeated words, the hesitations, mumblings, and so on, and how much they make use of prior knowledge about each other and the topic discussed. Listeners frequently perceive words that they do not actually hear.  If the same utterances with words in random order (ie meaningless) were transcribed by human and computer, the computer would likely do better.

 

Number crunching is not the solution

The problem we have is that we cannot continually improve the understanding of speech by continually improving the recognition of words. It is like trying to get a car with flat tyres to go faster by putting in a larger engine. The engine is not the critical path and it is cheaper and more effective to pump up the tyres than improve the engine.  So too with speech. In order to behave and understand like a human, the machine needs more information, not better algorithms or more computer power to improve the word recognition.

Many banks would argue that it doesn’t matter if the customer has to repeat an account number 10 times during a telephone banking transaction because it is not costing the bank any more than saying it once.  But here again, the human factors are all-important. It is no consolation that repeating something 10 times might ultimately bring down a customer’s bank charges – eventually the customers will vote with their feet.

 

.. but adding information is.

So what is the solution? The remedy  is that AI must be applied to the problem as a whole, not just to isolated parts. Taking ASR as an example again, by using readily available information contained in email correspondence, speech recognition performance can be improved far more than by improving the ASR algorithm or running it on a bigger computer.  The emails can be used to effectively train the ASR system on the types of words that are exchanged and the subject matter being discussed. In addition, text-based messages can give valuable clues to the grammar being used – the sequences of words, the likely combinations of words, etc.  In short, the context of the discussion.  Being able to share email and voice traffic is already possible, but is not yet being widely applied, and yet could dramatically benefit both financial institutions and their customers by helping a computer better understand the context of a conversation.

Speech recognition is just one example of an AI process that often falls short on expectation. There are many more applications of AI that can be improved by taking a holistic view, not just the bits we like. AI is all about emulating humans, not number crunching. To do this, we need to understand as much as we can about the human process we wish to automate.

Looking at how the human processes information can yield benefits in many areas of IT. For example, some of the largest advances in video data compression came from an understanding of what the human eye can perceive rather than the mathematics of information theory.

In summary, AI is not about building more and more powerful neural networks, it is about convincing a human that the computer is doing as good or better a job than another human would. And to achieve this, we must tap as many information sources that the human has available – which with some lateral thinking are available to the machines too. If this information is not present then we cannot compensate by continuously improving just some parts of the process. We must either find more context or rethink the solution. Until this happens, ASR may be subject to the law of diminishing returns.

 

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BIOMETRICS: BALANCING SECURITY WITH CONVENIENCE

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Jean Fang, Authentication Product Manager and Joël Di Manno, Authentication and Biometrics Laboratory Service Line Manager at Fime

 

From a person’s face to their iris, voice or fingerprint, biometric solutions are giving us new ways to authenticate ourselves when using a device or making a payment. Research suggests that the global facial recognition market alone will be worth up to $13.87 billion by 2028, with other modes of authentication following a similar growth pattern.

The trend towards biometric authentication has been further accelerated by the global pandemic. Hygienic touchless identification solutions have become critically important. And, with customers already familiar with using biometric solutions on their phones, the growth of this industry only looks to continue. In this blog we will evaluate this growth and discuss some of the potential opportunities and challenges that lie ahead.

 

Addressing fragmentation

Biometric authentication is an innovative and rapidly evolving technology. However, the speed with which it has developed brings with it unique challenges. The technology operates within a largely non-standardized ecosystem, meaning that it is fragmented on many fundamental issues. Little regulates how manufacturers and developers create and implement solutions.

The fragmentation that currently exists means that developers and manufacturers face three main challenges:

  • Increasing interoperability and adaptability.
  • Looking for a standardized certification process.
  • Formulating uniform benchmarking practices to allow developers to compare key performance metrics.

Addressing these three concerns will help create a simpler, more standardized biometrics ecosystem, allowing innovations to reach the market quicker and cheaper.

 

Security vs UX

The most notable emerging use cases for biometrics are payment authentication, access control and government administrative projects. All three require access to extremely personal data, and therefore it is essential for them to have very strong security.

Perhaps the major selling point of biometric solutions is their ability to provide the necessary security while enhancing the user experience (UX). However, overly-stringent security can negatively impact the UX. Therefore, there must be a trade-off between the two.

The best way to understand this balance is by comparing the False Acceptance Rate (FAR) with the False Rejection Rate (FRR). A low FAR gives a good indication that a solution is secure, as it only accepts the right user. Meanwhile, a high FRR provides a very high level of security, but creates friction – and potentially damages the UX – as it prevents genuine individuals from authenticating. Striking the right balance between these two is crucial to maintaining high security standards without creating a poor UX.

 

Multiple modalities for multiple solutions

The adaptability of biometric solutions means that original equipment manufacturers (OEMs) must constantly evaluate the available solutions and determine which is the best for their device. OEMs must develop a clear strategy to determine which biometric modality is best suited, factoring in cost, UX, speed and security.

However, there are also situations where device manufacturers may want to utilize multiple modalities. This can benefit both the UX and security of their solution, as it can address numerous concerns:

  • It can account for environmental concerns. For example, if a user is wearing gloves due to cold weather, making fingerprint scanning impossible, authentication can be achieved another way.
  • For high-risk authentications, multiple modalities can be utilized at once to achieve heightened security.
  • It also allows for adaptability regarding any future changes to the industry or regulatory requirements.

Determining which modalities will best serve a device and its deployment is one of the major challenges OEMs and developers face. The current lack of standardization only further complicates this. However, as the field grows and becomes less fragmented, the multimodality of biometric solutions will facilitate innovation and security for years to come.

 

Just the beginning

Biometrics have become a fixture of consumers’ everyday lives, but the huge successes seen in mobile technologies have not yet translated to other sectors. Innovations continue to push the boundaries of how we use biometrics, as they are rolled out in workplaces, homes and transportation. To reach widespread adoption, companies need to provide customers with assurance that their products are secure. Standardized testing and certification lay the foundations for this.

Biometric technologies continue to evolve daily, which means that the regulations and requirements that govern them need to do likewise. Standardizing the entire ecosystem would allow developers and OEMs to regularly test their products against uniform benchmarks, ensuring they are secure while keeping costs down and launching quicker.

 

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HOW CAN THE PAYMENTS INDUSTRY PREPARE FOR SCA WITH BIOMETRICS?

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By Vince Graziani, CEO, IDEX Biometrics ASA

 

Significant developments are afoot in the retail and payments industry, with vendors needing to prepare for Strong Customer Authentication (SCA). It’s set to be the most significant change to how people pay for things, not only online but also for card-present retailers across Europe. The deadline for compliance with the regulation has recently been extended again, this time to March 2022.

This is now the third time the deadline for retailer compliance has been pushed back, with the Financial Conduct Authority (FCA) worried vendors are not prepared for the new payment security approach. Which raises the question, will SCA every really take off?  Well, for retailers the extended deadline can be viewed in a positive light. The fact that there are now a further ten months to pilot and then launch their response gives retailers more time to adapt their authentication and verification tools. But it’s also a benefit for banks and payment providers too.

The ongoing delay to the SCA will give the payments industry extra time to prepare for the rollout of the directive so they can deliver a secure SCA payment option to consumers. If the payment ecosystem fails to use this time to prepare or implement the right technology to comply with this new ruling, it will open consumers up to a significant threat of card fraud.

 

Vince Graziani

The challenges faced within the retail space

There has been a large amount of focus on the implications of SCA when shopping online; however, face to face purchases will also need to be revisited. Even when using a card physically, SCA will require two-factor authentication for every purchase made over the contactless limit. This additional layer of protection provides a more stringent authentication process that will help to keep millions of accounts safe from both traditional fraudsters and cybercriminals.

Two-factor authentication means that not only will the user need to provide their details when making a purchase, they’ll also have to confirm their identity with:

  • something they know (a PIN or password),
  • something they have (such as a smartphone),
  • or something they are (biometric face or voice features or a fingerprint).

Once implemented, this will be beneficial in protecting consumers, however, getting to this stage will be a challenge. The requirements are set to cause widespread disruption to the retail space. The introduction of SCA will require in person merchants and card issuers as well as online Payment Service Providers (PSPs), such as PayPal and WorldPay, to have in place the technical enhancements and testing needed by the deadline.

 

Educating the shopping public on SCA

This presents a significant logistical challenge; maintaining effective fraud prevention while keeping an optimised customer experience is not easy. But perhaps the biggest challenge of all is that consumers themselves still aren’t entirely aware of SCA or what will be expected of them come March.

The introduction of SCA demands collaboration within the industry to educate consumers, but ultimately it is up to payment providers to provide a reliable, secure and SCA-approved method of payment to consumers. Providers must also ensure that the method they choose is not only up to standard but is affordable and accessible to all.

 

Preparing for the future of secure payments with biometrics

Biometric payment cards offer the answer for payment providers to help prepare for SCA. Not only will these cards – with inbuilt fingerprint sensors to verify ownership – provide strong customer authentication, but they also come with the added benefit of convenience. Validating your payment with a fingerprint speeds up the transaction process and removes the requirement of PINs or the use of a smartphone.

Biometric fingerprint payment cards offer banks and payment providers, an opportunity to embrace payment innovation that will help them meet these new secure forms of authentication with confidence and ease.

It is worth noting that some payment card manufacturers, such as IDEMIA, are already preparing biometric payment card solutions. These will be ready for banks and card issuers to adopt so they have the time they need to pilot and roll out the new payment method before the new SCA deadline is imposed.

The FCA has also outlined previously that long-term authentication through biometrics and mobile app-based solutions is the future of secure payments. The use of biometric payment cards to authenticate online payments will offer an important way for retailers to balance security measures that comply with the SCA regulation whilst also delivering ease of use for the consumer.

 

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