The alarming prospect of deepfakes impacting public sentiment and potentially affecting the results of India's Lok Sabha elections has sparked concerns within the cybersecurity community. With Indian citizens in the process of choosing a candidate aligned with their perspectives, the prevalence of deepfakes and generative technologies provides manipulators with a convenient means to produce and circulate authentic-looking videos depicting candidates engaged in actions or making statements that are entirely fabricated.
The Deepfake threat in politics
The use of deepfakes in politics is particularly alarming. Imagine a scenario where a political candidate appears to be giving a speech or making statements that have no basis in reality. These AI-generated impersonations, based on a person’s prior videos or audio bites, can create a fabricated reality that could easily sway public opinion. In an environment already riddled with misinformation, the addition of deepfakes takes the challenge to a whole new level.
For instance, the infamous case where Ukrainian President Volodymyr Zelensky appeared to concede defeat to Russia is a stark reminder of the power of deepfakes in influencing public sentiment. Though the deception was identified due to imperfect rendering, there is no way of knowing who believes it to be true even after being disproved, showcasing the potential for significant political disruption.
Deepfakes as a danger in the digital workplace
Employees, often the weakest link in security, are especially vulnerable to deepfake attacks. Employees can easily be tricked into divulging sensitive information by a convincing deepfake of a trusted colleague or superior. The implications for organisational security are profound, highlighting the need for advanced, AI-driven security measures that can detect anomalies in user behaviour and access patterns.
The double-edged sword of AI in cybersecurity
However, it's important to recognize that AI, the very technology behind deepfakes, also holds immense capabilities to help hackers discover cybersecurity loopholes and breach business networks. While AI may help discover new vulnerabilities for threat actors, it also can be used to discover counter-measures, such as identifying patterns in data that would have otherwise gone unnoticed.
A system can then flag the potential Deepfake content and remove it before it achieves its goal. This can help bridge the global skills gap in cybersecurity, enabling analysts to focus on strategic decision-making rather than sifting through endless data.
Data dilemma
The proliferation of deepfakes feeds into the broader issue of fake news and bots, adding one more aspect to the inability of people to recognize legitimate sources from manipulated ones. The result of a news story by well-crafted AI and repeated by a deepfake can lead to public distrust or even incite mass unrest.
But let’s not forget that in the digital battlefield, AI is a weapon wielded by both defenders and attackers. Deploying algorithms to confirm unmanipulated data or discover mitigation efforts based on patterns in data can open new use cases for secure AI growth.
Regulatory-guided solution
Combating deepfakes requires a multifaceted approach that India lacks with its IT Act.
Legal frameworks specifically targeting the malicious creation and distribution of deepfakes are essential, along with international cooperation to manage the transnational nature of digital media. In the realm of technology and AI, ethical guidelines must be established to regulate the development and use of deepfake technologies. Media authentication frameworks, public awareness campaigns, and media literacy initiatives will be crucial in empowering individuals to distinguish between real and synthetic content. This collective effort is key to maintaining the integrity of digital media and the broader democratic process.
A business-first solution
The global call for regulating generative AI, including deepfakes, is growing. However, it's important to recognize that comprehensive regulations primarily govern those within an industry, not individuals who operate outside legal boundaries.
Companies must prioritise AI-driven cybersecurity solutions as part of a broader, company-wide approach that intertwines safety with quality across all aspects of their operations. From online behaviour to development processes, a centralised AI- ingested understanding of an organisation’s baseline is crucial. Such technologies can identify breaches in real time, whether perpetrated by external threat actors or employees misled by deepfakes. This proactive stance is essential for maintaining integrity and security in a digital landscape increasingly complicated by AI technologies.
