In the early days of internet commerce, customer and user reviews were critical to the evaluation of a person or product. These reviews allowed you to research the quality of a product, or whether a person providing a service was trustworthy and good at their job. Nearly every platform where people provide a product or service utilizes a rating system. This is the cornerstone of sites like Ebay, Amazon, Freelancer, and many others. Ratings and reviews have served a very important purpose in providing a bridge between the anonymity of the internet and being able to trust what someone is providing. In the early days that was perfectly acceptable, but over time this has become one of the most abused and manipulated aspects of internet commerce.

Yes, most real people who leave reviews use the process in the manner it was intended, but there is an ever growing issue with the review process that is harming everyone. Fake reviews and accounts, bots, and scams are becoming commonplace in the world of internet commerce. To use Twitter as an example, a study published by CNBC revealed at least 48 million Twitter accounts were fake/bots. You can view that study here. The problem is not just limited to Twitter. Paid reviews are a big business and has incentivized the growth of huge review farms around the world. Reviews are becoming increasingly difficult to trust due to the prevalence of these fake reviews. The Latium Team has found a transparent way to solve this issue by taking the human review out of the equation all together.

Latium Will Utilize A Revolutionary Reputation System To Rate Users

The Latium Platform will utilize a proprietary reputation system in order to rate its users. User scores range from 0–1000 and are based on many different data points which are systematic, not opinion based. These include, but are not limited to, amount of jobs completed, hire rate, payment time, task value, and worker/employer diversity. The goal is to provide a simple single number, so they can evaluate quickly without additional research. Providing a simple number for users to gauge who they are potentially working with adds another layer of scrutiny to prevent fraud.

The best example of this is the US FICO credit score system. User scores will be changed based on actions and also lack of action. The system will inherently award long-term users with better work/employment histories, while also discouraging spam and the creation of fake accounts. The system will begin as a proprietary algorithm and over time be totally AI driven. Ultimately the AI will create new rule sets to mitigate risks before they even present themselves, thus creating a reputation system that truly does not require human intervention in any way.

If you would like to learn more about the Latium Reputation System, or the Latium Project and how to become involved, please visit Latium.org.

You can also follow us on Twitter and join our Telegram Chat to keep up with the latest news.