In the Counterfeit Boom, AI is on Both Sides
AI cannot recreate a designer handbag, but it can give counterfeiters the tools to do so. There is more to counterfeit now with e-commerce and advancing AI technology. Deepfakes run rampant online, replicating people’s signatures, transactions, voices, and appearances with a few savvy clicks.
AI can also discover criminals creating illegal copies of digital products and identities. It is an issue industry professionals and curious minds must prioritize for the safety of personal data and livelihoods. Here’s how to fight counterfeit products with AI.
The Role of AI in Counterfeit Detection
Experts must bolster AI tools to be more proficient at being an anti-counterfeit technology than one to make illegal products. The technologies that help AI fight counterfeiters include:
- Text analysis via natural language processing in large language models
- Cross-referential image recognition
- Neural networks for detecting image inconsistencies
- Machine learning to see counterfeit trends with big data analysis
- Blockchain for transaction verification and smart contracts
The tools work together to identify AI-generated product photos or measure the sync between audio in a video to the mouth movements of the individuals. The benefits are as significant as the data set it references. The more robust and curated the information is, the more accurately it can detect specific types of counterfeiting. Experts train AI specifically on how to fight counterfeit products. The data set only helps it if it’s well-trained and supervised.
A Mongolian pharmaceutical company engaged in a pilot study in 2018 to detect fake drugs, an initiative with the potential to save hundreds of thousands of lives. The technology hit everyone related to the projects, from stakeholders to distributors. Results led to the creation of consumer apps to prevent medical fraud.
Blockchain can encrypt electronic records to protect manufacturing parts or secure corporate contracts between business-to-business partners. It affirms customer loyalty when they know they get OEM parts from distributors.
AI-Assisted Counterfeiting
AI is equally proficient in creating counterfeits. It uses the same technology to detect and develop fakes. AI digs through its deep data wells to construct believable deepfakes and false media. These examples show the breadth of AI-assisted counterfeiting:
- Smart speakers with compromised security, replicating Alexa or Google Home
- At-home healthcare devices producing inaccurate results, such as blood sugar monitors
- Programs that steal data, such as fake operating systems
The ethical quandaries concerning abusing AI for this purpose are why anti-counterfeiting technology is a high priority for governments and companies. Deepfakes convince customers of falsehoods about product specs or create convincing reviews or testimonial videos from representatives. Detecting counterfeits is sometimes more difficult than crafting, as it relies on AI to see the most subtle differences while analyzing.
Every corporate, governmental, and personal identity is at potential risk of having their images irreparably tarnished. Safety is a more significant concern, as AI manipulation and counterfeiting bring undue stress and attention to guiltless parties.
The Battle Between AI and Counterfeiters
Each side knows what the other is capable of, resulting in countermeasures. The moment a cybercriminal drafts a strategy for avoiding counterfeit detectors, industry professionals reinforce them, making blockchain stronger to track and natural language processing more proficient at spotting textual inconsistencies.
The relationship between AI and experts must remain strong. The physical counterfeit goods market has an estimated value of $2.81 trillion and gets a boost from $323 billion in digital infringements — it is a monumental task to isolate. The counterfeiting war will soon have a victor if the justice-led side gives up on a technology meant to advance global good.
Therefore, participants in this must maintain mental resilience and determination to create the most competent and well-trained AI possible, preventing hallucinations and oversights in every corner. AI still requires human intervention for anti-counterfeit technology. The motivation must stay strong as experts training AI act as another set of eyes during counterfeiting investigations to execute forensics or question decision-making.
Laypeople surfing the internet, subject to targeted content based on algorithms, must train themselves to question every byte of data they interact with. Stopping AI counterfeiting requires an effort from all fronts, including:
- Regulatory bodies
- Government agencies
- IT professionals and cybersecurity analysts
- People curious about ChatGPT
- Criminal investigators and forensics experts
- Data scientists
AI’s Dual Counterfeiting Purpose
AI has the power to be an anti-counterfeit technology and create fake content and products with alarming accuracy. Casual users of generative AI, developers, data scientists, and government officials who investigate fraud cases must collaborate to identify trends and stop counterfeiting habits. Spreading awareness is a potent first step in minimizing AI fakes and their impact, allowing productive efforts to fix AI’s reputation to resurface.
Originally posted on OpenDataScience.com
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