While there are undeniable and incredible opportunities for AI-enabled electronic signatures (eSignatures), it’s crucial to avoid looking at the possibilities with rose-tinted glasses.
Signature forgery is nothing new, with noteworthy examples suggesting how easy it can be to conduct it fraudulently and maliciously. However, AI forgery detection software exists, which provides some reassurance given how it works, but there are risks to deploying this without due diligence. Key factors should be considered heavily before any AI solution is deployed on an incumbent eSignature solution, and it’s easier said than done.
Businesses can beguile at the huge cost- and time-saving benefits associated with automating parts of their business, including signature collection. While the integration of AI promises to streamline and automate many legitimate parts of document and contract signing, safeguards must be firmly in place to prevent fraud, abuse, and, in extreme cases, misinformation. Failing to cast a watchful eye over AI’s evolution in this space can have dire consequences.
AI has been at the heart of notoriously controversial misinformation campaigns and financial scams, and it’s even more worrying how convincing AI-powered content like text, video, or audio can deceive even the most cyber-aware individuals. Businesses facing heavy legal and regulatory scrutiny, however, are under an even larger microscope, which is why they should be acutely aware of all the emerging and developing risks around AI and signature validity.
The Rising Risk of AI-Enabled Forgery
AI is powered by machine learning (ML), which enables it to study patterns with razor-sharp accuracy in its datasets. As a result, AI tools can create realistic and seemingly legitimate signatures, as well as long-format content like documents, articles, and whitepapers.
However, this is just the tip of the iceberg, as sophisticated AI image and video generation tools have also proliferated in recent years, casting doubt and eroding trust among users. What’s more, there are widespread underlying concerns that criminals could leverage AI to impersonate individuals and commit fraud. This poses a huge cyber security and data validity concern.
High-profile examples have emerged recently of AI image and text generators used to spread fake news, misinformation, and disinformation, and generate synthetic media. It doesn’t help that many AI tools are heavily rooted in unconscious biases which can laterally appear in any AI-generated content. This only exacerbates the potential harm that exists at scale, especially when you consider the lack of regulation currently in place.
Here is what Craig Chapman, Senior SEO Manager at used photography equipment seller MPB had to say concerning the rise in AI content and how it’s affected their business: “At MPB, trust is everything. We’ve seen firsthand how the rise of deepfakes and AI-generated imagery threatens the authenticity that photographers and videographers rely on. When advanced technologies can manufacture believable but false worlds, how can any image be trusted?
That’s why we deploy strict seller and buyer standards and visual inspection protocols for every piece of equipment, to ensure the integrity of all media on our platform. We also advocate for ethical AI standards because innovation need not compromise integrity or community. However, the shift that AI image generation has had on creatives using our platform has been nothing short of profound.”
While the imagery risks of AI are apparent, the threat of forged and fake eSignatures generated by machines, as opposed to legitimate signers, looks set to increase the way things are going. Without proper regulation and security, trust and legal footing can be compromised significantly.
The High Stakes of Forged eSignatures
Falsified and illegitimate eSignatures, enabled by irresponsible and reckless AI use, can cause prolific problems for businesses, particularly if they rely heavily on document automation.
Financial losses: Forged eSignatures on digital contracts, agreements, or approvals, can lead to the unauthorised and illegal transfer of funds or collateral. Subsequently, malicious actors can seize assets with ‘transactions’ having bypassed standard security protocols and not raised any cause for concern, due to the seemingly innocuous signature.
Legal liability and accountability: Documents and agreements secured with false or unverified eSignatures lose all legal authenticity. However, relying on them could still open up an organisation to lawsuits, fines, and stakeholder or investor scrutiny.
Reputational damage: Invariably, organisations on the receiving end of legal or regulatory fines will be under even more pressure to regain public trust. If customer or partner signatures have been fraudulently compromised, the short- and long-term risks can be severe.
The Role of Responsible AI Governance
Preventing eSignature fraud from propagating to such unprecedented heights requires businesses in every sector to adopt more stringent verification, validation, and oversight.
As a starting point, organisations should conduct regular risk assessments to proactively identify and mitigate potential dangers from AI systems and biased datasets. Ensure that any AI models they utilise meet regulatory standards as well as in-house policies around transparency, data protection, and data integrity, will also be vital. As is the case with any AI solution on the market, restricting its use to specific silos in an organisation will allow greater control and testing of its authenticity and automation ability, thus enabling firms to evaluate their performance for misuse.
Proper data protection and integrity measures should be implemented to ensure that personal information used in AI-powered eSignature solutions is secure. This includes validating the encryption protocols used when obtaining and transmitting data between parties.
Businesses are still bound by legal requirements and industry regulations, even if they deploy AI. The EU, as an example, is proposing a universal legal framework for AI use across geographies and sectors. However, until then, depending on their areas of operation, they may need to evaluate whether they will be breaching any standards when enrolling AI into their eSignature processes. Some industry bodies stipulate clear instructions and best practices when using AI, given how prevalent it is in the market today, but for others, it’s more ambiguous.
Remember that AI as we know it today is incapable of independent thought, and lacks the complexities and experiences that formulate human activity and experiences. AI is only as intelligent as the data that it learns from, or the tasks that it is given. Organisations must consider the validity and objectivity of data, stipulating clear and specific processes for the AI system that will be using it. Doing so will limit any AI-generated outputs to be a security or data protection concern.
Carefully review your data to train algorithms to avoid creating misinformed judgements or exacerbating existing unconscious biases. As a primary initiative, it would be wise to involve humans to supervise and test an AI program’s execution and validity before deploying it widely across your organisation.
The Future of Secure eSignatures
AI promises innumerable benefits but there are evolving risks around eSignatures and other legal means of verification. Organisations must take methodical, considered steps to secure processes and enforce responsible AI use. With the right safeguards and governance in place, companies can take full advantage of automation and improve productivity within their teams while reaping the benefits of seamless, trusted, and legal signing experiences.
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Dakota Murphey is a Brighton-based, established freelance writer with experience in business growth and a strong interest in all things digital. Aside from her love of writing, she loves good times with family and friends and admits to being a bit of a film buff.