AI or Not

    5 Generative AI Predictions for 2024: AI Detection, Risk, Compliance, Video and Election Effect

    AI or Not's 5 Generative AI predictions: AI-Generated Video Takes a Quantum Leap Forward, How 2024 Elections Will Expose Generative AI Threats, Generative AI Fakes Will Disrupt AML/KYC Processes, AI Detection Joins the Fight in Cybersecurity and Fraud Systems, AI Will Be a Corporate Windfall but Not So Much for Employees

    5 Generative AI Predictions for 2024: AI Detection, Risk, Compliance, Video and Election Effect

    The dizzying pace of technological change often leaves us equal parts amazed and concerned about what the future may bring. As generative AI continues its meteoric rise, many wonder whether 2024 will usher in a new era of prosperity or new avenues for misuse.

    With the unique view that we have here at AI or Not, our predictions cover the positive potential and consider proactive strategies to mitigate risks. Here are our top 5 Generative AI predictions for 2024:

    1. AI-Generated Video Takes a Quantum Leap Forward
    2. How 2024 Elections Will Expose Generative AI Threats
    3. Generative AI Fakes Will Disrupt AML/KYC Processes
    4. AI Detection Joins the Fight in Cybersecurity and Fraud Systems
    5. AI Will Be a Corporate Windfall but Not So Much for Employees

    AI-Generated Video Takes a Quantum Leap Forward

    From deepfakes to the jaw-dropping realism of ChatGPT dialogues, generative AI made astounding progress in replicating textual and vocal communication over the past few years. Yet synthesizing realistic video has proven far more challenging for machines. In 2023, even the best AI-generated video appears glitchy - full of distorted faces, artifacting and surreal scene changes.

    But by 2024, AI generated video will see innovation across computer vision, reinforcement learning and generative adversarial networks. 

    What new doors could flawless AI-generated video unlock for Hollywood’s special effects, the gaming industry’s cut scenes, or smartphone apps that let anyone star in a dance video? What new risks arise when malware can impersonate your boss in a custom-tailored video call?

    Imagine the scenarios this will unlock: a CEO delivering a heartfelt apology from a beach in Fiji they never touched, a political candidate morphing into their opponent mid-speech, or news footage so seamlessly manipulated you'll question the very fabric of reality. 

    We’ve already seen snippets (no pun intended!) with fake MrBeast and fake current and former presidents.

    While AI detection tools will surely advance in tandem, the arms race of fakes versus forensics continues. 

    For AML/KYC compliance professionals, this advancement means rethinking the way we validate and verify digital content. Gone are the days when a grainy video was a red flag for fraudulent activity. Now, we're dealing with hyper-realistic content that could pass for your next-door neighbor – or even you.

    Compliance professionals already had to detect GenAI driver's licenses that pass biometric scanning. Now a video interview with your "client" looks to be straight out of Hollywood casting central, passing video KYC. 

    In regions with stringent AML and KYC regulations like the EU, financial institutions may scramble to bolster their authentication safeguards. Required video KYC is no longer fraud-proof with adversarial networks producing videos customized to spoof identity documents or even biometric facial recognition checks that link the video call to a valid government ID.  

    But it’s not just about fraud prevention. AI-generated video can also be used to train employees, create virtual avatars for customer service, and enhance the security of online transactions. 

    Yet rather than react in fear when faced with such a potentially disruptive technology, responsible stakeholders should lead with empathy, envision positive applications, and enact thoughtful safeguards. If we temper ingenuity with wisdom, AI-generated video could become an instrument of creativity, connection and understanding at scale.

    How 2024 Elections Will Expose Generative AI Threats

    2024 elections in the US are approaching, along with 40 other global elections. As the world eagerly awaits the outcome, there is another aspect that will capture the attention of both voters and experts alike – the role of generative AI in shaping the political landscape. While generative AI brings many benefits, it can also be exploited for malicious purposes, raising concerns about the integrity of the electoral process.

    One of the most alarming consequences of generative AI is the rise of deepfakes. Deepfakes, which are AI-generated videos or images that convincingly manipulate or replace the original content, have become a growing concern in recent years. These sophisticated creations have the potential to deceive the public and undermine the trust in political candidates and democratic processes.

    The ‘Fake News’ problem of 2016 will be magnified with Generative AI.

    As the campaigns heat up and the political atmosphere becomes increasingly charged, there is a legitimate fear that generative AI could be misused to spread misinformation, fabricate compromising videos, or manipulate public opinions. The negative impact of such AI-generated content on elections cannot be overlooked, as it has the potential to sway voters, distort the truth, and disrupt the democratic process.

    If 2023 was the year we began exploring how GenAI can have a positive impact on our work and lives, the 2024 elections will, undoubtedly, be a turning point in how we perceive the negative impact of generative AI. It's a wake-up call to bolster our defenses with AI detection and refine our tactics. 

    So while the 2024 race may highlight previously unfathomed vulnerabilities, it can also push us to demand integrity alongside innovation as AI propels society into new frontiers.

    Generative AI Fakes Will Disrupt AML/KYC Processes

    Few industries have more at stake on validating identity and document authenticity than AML/KYC compliance sectors. Yet the accelerating proficiency of generative AI in crafting credible forgeries threatens to undermine long-standing fraud detection workflows.

    Whether an artificially generated driver's license, pay stub or utility bill - such fakes display no obvious "tells" through metadata analysis or content inspection. And they can be dynamically customized to match specific identity attributes submitted in new account applications.

    This represents a sea change challenge for institutions entrusted with vetting legitimacy before transferring assets or approving loans. Their very business models depend on reliably filtering unlawful elements while facilitating transactions for lawful customers.

    Yet refusing all but a narrow band of identity documents as verification tools also hampers financial access for marginalized groups. And requiring extensive supplemental proof raises costs and irritation for account holders.

    As Generative AI technology becomes more advanced, the ability to create realistic deepfakes will become more accessible, making it easier for fraudsters to create fake identities, documentation, and even video footage. This poses a significant challenge for compliance professionals who rely on these materials to verify the identity of customers and prevent money laundering.

    In this new era, traditional AML/KYC methodologies will need a serious upgrade. We need to integrate advanced AI detection into our compliance arsenal. This means not just verifying identities but understanding the patterns and anomalies that AI fakes leave behind.

    By integrating such AI detection into existing compliance workflows, responsible institutions can mitigate risks of dismantled trust while retaining speed and convenience for lawful customers. 

    AI Detection Joins the Fight in Cybersecurity and Fraud Systems

    As exponential improvements in synthetic media unlock new attack vectors for fraudsters and cybercriminals, systems reliant on content validity face profound threats. From doctored evidence submitted to insurance agencies to spoofed video calls deceiving banks, the range of generative AI misuse spans industry and intent.

    Yet while uses of AI to counterfeit and impersonate present novel vulnerabilities, applications of AI to detect and defuse such threats brings new hope.

    By exposing Generative Adversarial Networks to vast datasets of real and fake content, forensic classifiers discern subtle signals unnoticeable by people.

    Deepfake detectors with AI X-ray vision: Remember those clunky "I blink, therefore I'm real" deepfakes? They'll be as easy to spot as John Wick wandering in the desert. AI will analyze pixels, speech patterns, and even subtle body language, exposing synthetic imposters with its own spotlight. 

    Linking such detection engines with existing identity verification, surveillance and authorization frameworks promises to counterbalance rising generations of identity theft. The technique even extends to entirely new modalities like code repositories, where a generative model's subtly different variable naming convention betrays its artificial origins to trained detectors.

    As cybersecurity and fraud systems integrate the latest protective algorithms into their tech stacks, we inch towards restoring stability amidst turbulent change. 

    AI Will Be a Corporate Windfall but Not So Much for Employees

    In 2023, corporations large and small took notice in AI. The breathtaking pace of AI progress looks set to profoundly reshape business landscapes in 2024 and beyond. Generative models that synthesize content, decode patterns and optimize workflows promise immense profitability gains for companies nimble enough to adopt these tools. From slashing computing costs through efficiency to altoring entire supply chains via predictive analytics, the benefits appear boundless.

    The integration of AI technologies is expected to bring significant efficiency gains and growth in the year 2024.

    While AI holds great promise, not all employees will benefit equally from these advancements. Certain job roles that involve repetitive tasks or data analysis may be susceptible to automation, leading to potential job displacement for individuals in those positions.

    As AI becomes more prevalent, businesses must proactively address the challenges of workforce transition. Investing in reskilling and upskilling programs will be vital to ensure that employees can adapt to the changing landscape and acquire the necessary skills to thrive in an AI-driven economy.

    After all, the same generative algorithms excelling at legal briefs, product descriptions and even software engineering could theoretically undermine whole professional classes. Rather than upskilling employees, short-sighted companies may simply cut staff support roles.

    However forward-looking leaders increasingly realize business sustainability relies on balancing productivity with inclusivity across stakeholder groups, including employees. 

    This is an opportunity to evolve, adapt, and thrive in a world powered by AI, for both companies and its employees. Upskill and reskill to magnify individual impact coupled with AI.

    From exponential improvements in synthesized video, new creative frontiers to increasingly high-stakes electoral scenarios highlighting vulnerabilities of rapid change, the innovations forecasted next year promise to profoundly reshape society.

    Whether bolstering fraud detection systems with AI detection to balance threats of counterfeits or implementing structural supports like job retraining programs.

    At its core, realizing AI’s positive potential requires imbuing the optimism and ingenuity driving scientific advancement with the wisdom and empathy befitting our shared humanity.

    Onward together through times of change towards AI’s abundant promise!