Blockchain-powered recruitment platform LaborX has announced a partnership with the SingularityNET AI solutions developer to automate job search and hiring processes.

LaborX, which is a product of Australian company Chrono.tech, will use SingularityNET's AI solutions to analyze job candidate profiles in a faster and more comprehensive manner, streamlining the screening, selection, and hiring process. Current statistics indicate that each posted vacancy can attract from 1,000 to 2,000 candidates, making selection both time-consuming and inefficient. The application of AI is expected to improve candidate matching and significantly increase selection efficiency.

The modern labor market is still reeling from the effects of the COVID-19 pandemic. Considerable issues remain with screening and selection procedures, which are lengthy and often imperfect due to large response volumes, resulting in the sifting out of potentially valuable talent. Labor force participation rates have also remained stagnant since the end of the pandemic, posing challenges in both time and analysis terms before HR teams in the search for qualified professionals. In addition, the low degree of automation and inefficient AI integration leave little room in the HR domain for a human experience and a personalized, transparent, and communicative approach to candidate selection. To address these issues, LaborX and SingularityNET will test AI-powered HR software.

"AI technology is in a phase of rapid advancement and one after another area of human pursuit is being effectively automated by Large Language Models, neural-symbolic systems and other latest innovations.  At this stage, however, as AI takes on more tasks it also creates new forms of work for people to do – and there is a role for AI in helping match people needing work with the ever-shifting array of employment and contracting opportunities," noted Ben Goertzel, CEO and Chief Scientist at SingularityNET.

Smart use of AI solutions can significantly reduce recruiting workloads for hiring managers through automation, thus drastically reducing candidate screening and selection times. With refined and customized search parameters, the AI can single out talent pools with pinpoint precision and match candidates with employer requirements. Most importantly, advanced AI tools can neutralize screening bias, expand candidate sources, and enhance the recruitment experience, approximating it to human communication via the use of tuned chatbots.

"According to our estimates, labor and time costs for selecting the best candidate will be reduced by more than 100 times, and optimal parameter settings will allow AI to find a candidate in a matter of seconds, while currently it takes dozens of working hours," Sergei Sergienko, Chrono.tech founder and CEO.

The LaborX platform was designed by Australian company Chrono.tech to improve job search experiences by giving users access to safe and efficient tools, including digital contracts and escrow services. An embedded decentralized infrastructure provides a rating system that prioritizes searches and reduces associated fees to just 10% for freelancers and 0% for employers — a far cry from the 20% to 30% charged by traditional recruiting platforms. LaborX also provides dispute resolution and flexible payment systems, which include different currencies and digital assets across multiple blockchains. LaborX has already attracted over 120,000 talents and about 5,000 employers on the platform.

The partnership with SingularityNET opens up vast development possibilities for Chrono.tech. The company is planning to achieve full recruitment process automation within the framework of its services through the use of AI solutions and blockchain technologies.

About LaborX

LaborX is an on-demand work platform built by Australian blockchain company Chrono.tech. As a jobs marketplace hosted on the Ethereum network, LaborX connects freelancers and customers through smart contracts, enabling robust protections and efficient blockchain payments — wherever the different parties are based.