AI Creates More Jobs, but is Conditional without
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AI Creates More Jobs, but is Conditional without

Tuesday, September 8, 2020 5:00 AM
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LONDON, UK / ACCESSWIRE / September 8, 2020 / Machine learning is actively presenting job opportunities across the world. According to the World Economic Forum (WEF), Artificial Intelligence (AI) can create 58 million net increase of new employment by 2022. Besides tech giants such as Apple, Facebook, Google and Amazon are hiring Machine Learning engineers, other industries are increasingly leveraging this emerging technology at advanced levels. The huge demand for Machine Learning skills links to all kinds of fields, including but not limited to Financial Analysis, Smart Farming, Health Services, Online Education etc.,

COVID 19's AI Boom

During the current COVID-19 pandemic crisis, the appeal of remote work is surging globally. The massive needs for intelligent machines are growing in our workforce driven by the outbreak of telecommuting. When facing the huge dataset particularly, AI allows smooth cybersecurity checks, optimizes the pulling data process, and fosters telework with significant growth in efficiency and time-saving.

Apart from benefiting remote workforce, this powerful emerging technology has been deployed to fight against the virus. Microsoft AI can be used for early detection for COVID-19 and allocating limited resources such as medical supplies and hospital spaces with smart decision making effectively.

The future of intelligence machine is promising. According to Acumen Research and Consulting, the expected global investment of Machine-Learning-related products and services can reach up to US$76.8 billion by 2026. The application of AI technology will soon break new ground as the business industry keeps fueling the world market.

Skilled-biased Opportunity

While AI is agreed to have great potential, the application of this emerging digital technology marks a major shift in quality, location and requirements for the new roles. Machine learning, as a sub-technique under AI, automating analytical model building, is now increasingly adopted across industries. But not everyone stands to benefit automatically.

Based on Uria-Recio's TEDxIMU Talk, AI will continuously push human professionals up the skillset ladder into cognitive human skills. Process-oriented employment i.e., jobs with repetitive activities such as machine operators is now declining. Over the next decades, more than 80% of them will be done by intelligence machines.

In the meantime, a large number of job opportunity created involves cross-functional reasoning skills. When routine jobs are replaced by AI systems, businesses start looking for educated workers for new roles. Accordingly, the "human-machine collaboration" prefers applicants with advanced cognitive skills.

Workforce Transition

Given the increasing demand for creative and reasoning labors, job seekers should now upgrade their skills to adapt to new opportunities., a tech startup providing data training solutions, facilitates this workforce transition for workers. simplifies the advanced cognitive skills required for well-trained labelers. By interpreting complicated annotation rules, organizing the model into multiple stages, and dividing a big task into small pieces, lowers the needs for well-educated workers. The design of the ByteBridge's platform is very clear and easy-to-use.

Moreover, unlike the traditional machine learning companies hiring trained employees or managed teams for data labelling, incorporates blockchain technology into the data training solutions. ByteBridge's algorithm borrows the idea of a consensus mechanism from Cryptocurrency, distributing tasks to all users on the data platform. replaces technical quality check of trained labelers by a general agreement system. The platform assigns several people do the same work, and the correct answer is the one that comes back from the majority of labelers. A single task could be completed multiple times by different users. As a result, this process involves the contributions from hundreds of thousands of participants who work on verification and authentication of data labelling.

For the business with data training needs, provides options for accuracy levels. Benchmark measures the consistency among users. A score of 75 indicates 75% of users agree the label is correct. So higher benchmark scores can improve the accuracy of the data labeling task, implying the better quality of the data. This greatly improves the distribution efficiency through a consensus mechanism. And the customer can get a large amount of accurate data in a very short time.

Addressing Worldwide Technological Unemployment, not only provides work locally, is now tackling the skill-biased Machine Learning Revolution for all individuals around the world. With more than 100,000 registered users across Asia, North America, EU, and Africa, is offering tens of millions of online job opportunities based on big data and recommendation services all around the world.

Importantly, provides mutual benefit for business customers as well. This worldwide data factory "hires" all kinds of employees. Based on the education level, the language used, and competency-based assessment scores, the workforce can cover a wide range of needs from customers., as an intermediate data solution provider, bridges the massive new advanced roles with less-skilled works, bringing working opportunities around the globe.

SOURCE: TTC Foundation

TTC Foundation
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