This content originally appeared on HackerNoon and was authored by Zac Amos
Counterfeiting is a massive problem that damages economies, companies, and customers. Unfortunately, conventional anti-counterfeit measures like labels, hidden patterns, and tracking tags are easy to copy, rendering them useless. What does artificial intelligence do differently that makes it an effective tool?
How Big of a Problem Is Counterfeiting?
Counterfeiting is a global problem that affects every major industry. It happens everywhere, from the smallest flea market to the largest e-commerce platform. With the emergence of online shopping and international shipping, even small-business owners have criminals infringing on their intellectual property.
\ Counterfeits have multiple points of entry, which makes tracking them down challenging:
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- Suppliers hire subcontractors who create copies and supply chain professionals take cash to look the other way.
- Sellers accept returns, not realizing the buyer kept the original and sent back a fake.
- Wholesale distributors unwittingly take in forgeries and resell them en masse.
- Scammers set up stands on the street, promising passersby high-end products for impossibly cheap prices.
\ Sometimes, marketplaces are aware of counterfeiting but don’t do anything about it. Many want to preserve their identity as the neutral intermediary. They’re worried they’ll lose profits if they do anything to upset their tentative role in the buyer-and-seller balance, so they sit by to keep customers returning to their storefront — even if it means those people end up with fakes.
Does Counterfeiting Hurt Anyone?
Counterfeiting harms economies, companies, and individuals. Governments miss out on taxes, businesses lose revenue from potential sales, and customers end up with forged items. It’s not just handbags and brand-name shirts that get copied — pharmaceutical products, electronics, children’s toys, car parts, and kitchen equipment get faked, too.
\ Since counterfeiters aren’t held to the same standard as companies, they often make their copies in unhygienic conditions or use hazardous banned materials. These differences could have a severe, lasting impact when using fake items like baby carriers, vitamins, airbags, lithium-ion batteries, or bike helmets.
\ Unfortunately, such situations aren’t hypothetical. Federal investigators say there was recently a $230 million scheme to counterfeit lifesaving medication. The fraudsters swapped the real pills for an antipsychotic. One person temporarily lost the ability to walk and talk after unknowingly taking it instead of his regular prescription.
\ Each fake product that enters the supply chain results in a drop in revenue, domestic job losses, and misplaced customer anger. Seized counterfeit products had a total manufacturer’s suggested retail price of over $2.7 billion in 2023, highlighting how much companies stand to lose from each fraudulent sale.
AI’s Role in Anti-Counterfeiting Efforts
Algorithm-driven anti-counterfeit technology is necessary because detecting and preventing fake goods from entering the supply chain is too big for people to manage manually. Even an entire team of professionals can’t trace every shipment in real time as it moves across countries and changes hands — only AI can handle such a massive dataset.
\ Another reason to use this technology to detect and prevent counterfeits is because the counterfeiters already use it themselves. For instance, on Amazon, some listings have deceptive titles like, “I’m sorry, but I cannot fulfill this request. It goes against OpenAI use policy.” Businesses that want to eliminate fakes from the supply chain must fight fire with fire.
\ Committing to supply chain transparency is often one of the most effective ways to implement the processes needed for mapping and traceability. Companies would benefit from using chatbots to disclose their suppliers and logistics vendors to curious customers.
\ Besides, AI is a powerful tool capable of automating tasks and carrying out orders with little to no human intervention. While it is already incredibly popular, indicators suggest it will only continue gaining traction. According to one estimate, it’s expected to add $15.7 trillion to the global economy by 2030.
How AI Can Detect Counterfeit Products
AI can detect potential counterfeits in marketplaces by monitoring geolocation, product images, and sales figures. Advanced machine learning subsets like deep learning models can cover hundreds of listings in a second, picking up on anomalies like abnormally long shipping times or a high number of returns.
\ Natural language processing algorithms can analyze reviews or listing information and report potential counterfeiters. They can monitor online marketplaces for words or phrases that indicate someone is attempting to infringe upon another person’s intellectual property, meaning fake listings get identified and taken down much faster.
\ AI can provide real-time updates as shipments move through the supply chain when paired with Internet of Things sensors or tracking tools. This way, business leaders can receive notifications as soon as unusual activity occurs, enabling them to detect when forgeries enter the supply chain.
How AI Can Prevent Counterfeit Products
AI can prevent fake goods from entering the supply chain by flagging suspicious activity or triggering a predefined incident response like banning an anomalous listing or auditing logs. This technology can even identify repeat offenders, helping companies eliminate persistent counterfeiters for good. It can also stop people who knowingly buy forgeries.
\ About 52% of consumers intentionally purchase counterfeit items — and 21% of them do so frequently. Fortunately, AI can add value to products to make counterfeits less desirable. For example, chatbots can offer valuable insights, product details, or information on the dangers of fake goods to help people understand the importance of purchasing genuine goods.
\ Businesses can also embed this technology into their systems, vehicles, or packaging. A research group has already developed an AI-generated cryptographic code that can be embedded into containers of any size. It essentially makes counterfeiting impossible because it generates a hidden authentication code that is only detectable by the product’s manufacturers.
The Future of Using AI to Prevent Fakes
As more companies become used to using AI to detect and prevent counterfeit products in the supply chain, the number of applications will likely grow. Supply chain professionals should expect to see their role expand. It may one day become the standard technology for shipment traceability.
This content originally appeared on HackerNoon and was authored by Zac Amos
Zac Amos | Sciencx (2024-07-25T00:24:32+00:00) Using AI to Combat Counterfeit Goods in the Supply Chain. Retrieved from https://www.scien.cx/2024/07/25/using-ai-to-combat-counterfeit-goods-in-the-supply-chain-2/
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