Artificial Intelligence

How to Build Trust in AI with ID Verification

How to Build Trust in AI with ID Verification

Generative AI has attracted the attention of all over the world. Actually, 60% of businesses that have announced AI adoption are currently using generative AI. The leaders of today are trying to figure out the best way to integrate AI instruments into their technology stacks in order to remain relevant and competitive. AI developers are developing many more applications than before. However, given the rapid pace of adoption and the complexity of AI, a lot of issues regarding security and ethics are not being fully considered when companies rush to implement the most recent and advanced technology. In the end, the trust level is dropping.

A recent poll revealed that just 48 percent of Americans think AI is secure and safe While 78% believe they are either very or worried about the possibility that AI could be used to carry out malicious motives. Although AI is proven to improve workflows for everyday use, however, people are worried about the bad actors’ capability to alter AI. For example, capabilities that are fake are becoming more dangerous as the access of technology to people increases.

The mere presence of an AI tool isn’t sufficient. To allow AI to realize its full useful potential, companies must incorporate AI in solutions that demonstrate the responsible and sustainable application of technology in order to build trust with customers, particularly in areas like cybersecurity, where trust is crucial.

Also read: The Role of AI in Detecting Fake News: Combating Misinformation Online

AI Cybersecurity Challenges

Generative AI technology is advancing at an accelerated pace and the developers are only now realizing the importance of introducing this technology into the workplace as evidenced in the recent release of ChatGPT Enterprise.

Present AI technology has the capability of accomplishing things that were only spoken about in the realm of science-fiction not even 10 years earlier. The way it works is amazing and the speed of growth that is taking place is remarkable. This is the reason why AI technology is so adaptable and easily accessible to companies as well as individuals and, of course, scammers. While the capabilities of AI technology have spurred innovation, its widespread use has also led to the development of dangerous technology like deepfakes-as-a-service. The term “deepfake” originates from the technology that creates this special type of manipulated information (or “fake”) that requires the use of deep-learning techniques.

Fraudsters are always looking for the cash that will provide them with the highest return on investment, so any company that has a high chance of generating a profit will be their next target. That means that fintech companies, companies paying invoices, government services, and even high-value retailers of goods are always on the top of their list of targets.

We’re at a point where trust is at stake and consumers are becoming less trustworthy, allowing amateur fraudsters more opportunities to target. With the increasing access to AI tools and affordable costs, it’s easy for criminals at any level to manipulate other people’s images and identities. Deepfake tools are becoming easily accessible to the general public via deepfake websites and apps and the creation of sophisticated deepfakes takes only a few hours and a very low level of expertise.

Through the use of AI as well, we’ve witnessed an increase in accounts taking over. Deepfakes created by AI make it simple for anyone to create fake or fake identities, which could be celebrities or your boss.

AI as well as Large Language Model (LLM) Generative language software could be utilized to develop more sophisticated and devious fraud that is hard to identify and eliminate. LLMs specifically have led to an increasing number of phishing attacks that are able to speak in your native language. They also pose a danger that there is a risk of “romance fraud” on a large scale in the event that a user makes an acquaintance through an app or dating site however the person they’re chatting with is a scammer who has fake profiles. This is causing numerous social networks to think about the use of “proof of humanity” checks that are still viable on a large scale.

However, the security tools using metadata analysis, can’t prevent bad actors from committing. Deepfake detection relies on classifiers that seek out distinct features between fake and real. However, this method of detection isn’t as effective because advanced threats need more data points in order to be detected.

Also read: A.I Powered Document Verification and the Evolution of KYC in Telecom

AI and Identity Verification: working together

The developers of AI should be focused on using the technology to improve security measures that are proven to be effective. Not only does this create an improved and reliable application for AI but it will also be a more responsible usage – promoting better security practices and improving the capabilities of existing systems.

One of the most important applications of this technology is for identification verification. It is evident that AI threats are continuously changing, and companies must be equipped with a system that is able to quickly and effortlessly adapt and apply new techniques.

There are many opportunities to use AI using identity verification technology:

  • Examining key device attributes
  • Utilizing counter-AI to identify manipulators: To avoid being fraudulent and to protect sensitive data, counter-AI will be able to identify the manipulation of images that are incoming.
  • Relating the absence of data’ as a security issue in certain situations
  • Continuously searching for patterns across several sessions and clients

The layers of defenses offered by AI and technology and ID verification will investigate the user identity document, the network, and the device, thus minimizing the chance of manipulation due to deepfakes. making sure only authentic, trusted users are able to access your service.

AI and verification of identity have to work in tandem. The more comprehensive and accurate the data for training the more accurate the model becomes. As AI can only be as accurate as the data it’s fed with, the greater the number of data elements we can collect the more precise identification verification as well as AI can be.

The Future of AI and ID Verification

It’s difficult to be sure of everything online without confirmation from an authentic source. The foundation of trust online is the authenticity of your authenticity. The availability of LLMs or deepfake software carries an increased risk of fraud online. Criminal organizations have a lot of money and they can leverage the most recent technology on greater size.

Companies must expand their defenses, and should not be afraid to invest in new technology even if it creates some friction. There’s no longer just one defense option that they have to take a look at all details that pertain to the person trying to access the products, systems, or services and continue to monitor their journey.

Deepfakes are likely to continue to evolve and become sophisticated. Business leaders must be able to continually review the data generated by solutions to discover new fraud patterns and develop their security strategies constantly in line with the risks.

Written by
Aiden Nathan

Aiden Nathan is vice growth manager of The Tech Trend. He is passionate about the applying cutting edge technology to operate the built environment more sustainably.

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