Disinformation: Is Your Freight and Shipping Data at Risk?

AI( in particular, generative AI) has played a colossal role in enhancing and reshaping existing supply chains and shipping operations around the world. There's no room for debate on this matter. IDC estimates that more than 50% of G2000 OEMs will have redesigned their supply chains around AI by 2026.

But, while generative AI's benefits have been monumental, able to process vast, unrelated datasets to produce nuanced insights in seconds, its limitations and risks can't be overlooked either.

Disinformation is one of the most significant problems created by generative AI and remains one of the biggest risks to supply chain security and data integrity. I'm not suggesting that freight and supply chain organizations should give up on and eliminate gen AI from their existing operations, but rather they should be aware of the very real threat that disinformation poses to their freight data and operational efficiency.

Let's take a closer look at the risk of disinformation and how best to mitigate it.

The risk and spread of disinformation

Before we dive into misinformation, let's take a moment to clarify what we mean by disinformation. Simply put, disinformation is information that is fake, inaccurate or unverified and deliberately presented as accurate and factual. Remember, generative AI tools like GPT-3 and GPT-4 are large language models trained on a variety of data resources, including printed text, Wikipedia, and articles and data from the internet. Disinformation can be created by generative AI and presented as accurate, factual and verified when it's not.

With GPT and other LLMs pulling so much text from the internet, the potential for bias, errors and inaccuracies only increases, given how many unverified and unreliable sources of information there are.

However, when presented with a knowledge gap that it is unable to answer from its larger network, a gen AI tool can produce misinformation and present it as accurate and factual, even to the point where it creates fake sources or research to support its findings (a phenomenon known as "hallucinations").

When working with gen AI tools that are trained on extensive datasets, you may be risking your freight and shipping data's quality and integrity, and it could have a larger ripple effect across your entire shipment operations.

The risk disinformation poses to your organization

Whether you're a freight forwarder, carrier, or customs broker, relying on widely available gen AI software to augment your insights and processes leaves you vulnerable to misinformation.

For instance, if you receive a shipment request from a shipper and use gen AI to create a price request to send to a carrier, it may not use accurate or relevant data from its training data or the request itself to structure the price request.

The only way you would know is if you combed through the price request details and cross-compared them to the shipment request for errors and inaccuracies. If you don't spot them, that data error or omission can have a knock-on effect across the entire shipment process and your larger supply chain. This risk is ever present for any freight and logistics organization working with both shippers and partners to facilitate shipments.

The same goes for using gen AI for larger predictive demand forecasting and planning operations. Gen AI systems can make erroneous and inaccurate forecasts and predictions due to the unpredictability of the freight industry, but present them as indisputable and authoritative. The larger risk of relying on gen AI that uses unreliable data sources, synthesized data and other data risks becomes apparent now, and it can pose a serious threat to your data's integrity.

Stargo: safe, reliable gen AI capabilities at your fingertips

So, should freight and logistics organizations simply give up on the power and capabilities of generative AI? The short answer: no! Gen AI still offers powerful parsing and analytics capabilities that, when harnessed strategically, can enhance and guide your operations to better output, productivity and profitability. The key is being selective about the structure and type of gen AI you choose to incorporate into your processes.

Stargo, for instance, is a data centralization and management platform that "speaks" supply chain and offers structured, reliable gen AI capabilities. In addition to providing data structuring, enriching, correcting and centralization capabilities, giving you complete data accuracy and visibility, Stargo also has a Large Language Model.

Stargo's Large Language Model (SLLM) is trained on over 1 million samples from over 35000 real-world emails. The data used to train SLLM is accurate, reliable and verified, supervised by Stargo's dedicated team of data scientists. This means the data you're receiving from SLLM is verified and reliable, enhancing your data validation by adding an extra layer of security.

Book a demo with us to see Stargo in action and how we can use AI to enhance your shipment operations with zero risk of misinformation or data inaccuracy.