The majority of work in the digital age will be performed by Hybrid Intelligence, which combines human and artificial intelligence (AI), using complementary qualities that, when joined, boost each other. Artificial and human intelligence thrive at very different tasks. Moravec's paradox claims that it is relatively easy to make computer systems do well on IQ tests or play chess, but it is difficult, if not impossible, to give them the perceptual and movement abilities of a one-year-old kid.
Artificial intelligence is (still) limited in scope, but humans, in general, are not. It excels in performing precise, well-defined tasks based on a specific sort of data and in a controlled setting. In comparison to humans, who can learn from only a few instances and cannot operate with specialized data kinds, such as soft data, artificial general intelligence would require a large quantity of training data. This is where humans have an unrivalled competitive edge, and it is critical to remember this.
Because the brain and artificial intelligence use substantially different algorithms, each excels in ways that the other completely fails. Machine learning algorithms outperform humans in detecting complicated and subtle patterns in vast data sets. However, the brain can process information effectively even when there is noise and ambiguity in the input — or when situations change unexpectedly. This is why humans and AI must collaborate and join forces as hybrid intelligence. According to research, this is exactly how executives envision the future of work: AI, according to 67% of them, will enable people and robots to collaborate to harness their respective skills.
For its wide range of applications in practically every field, AI is a general-purpose technology. According to a recent worldwide CEO poll, the vast majority of large corporations (77 percent) are investing in or plan to invest in AI technology over the next 3 years. AI is not only the future of technology; it is permeating all aspects of our life.
It is difficult to predict how much of today's employment will be lost, but it is not unreasonable to assume that the percentage of jobs that will change is – 100 percent. Few jobs are immune from a change in the next 10 years, thanks to digitization and a hyper-connected society. Machines will do what they are best at, and humans will do what they are best at.
A new division of work is taking shape. Certain tasks could be done computationally, whereas others could be done in other ways. What AI can reproduce is what we do in the computing section of our brain, which is unlikely to be everything.
Computers today are nothing near the intellectual ability of a 5-year-old human, who can communicate intelligently about an infinite variety of topics while walking, picking up items, and identifying people's emotions. Computers are often trained to do specific tasks, but humans possess general intelligence, which they may exhibit by applying current information to completely new circumstances they encounter. Computers are still struggling with these issues. Because the future is unknown, and we should be cautious of strong forecasts that general AI will come within the next several decades, all applications of computers will need to include humans in some manner until that time.
Bitcoin 'Death Cross' Could Put the Crypto at US$25k Before 2022 Ends
Top 10 AI Skills that will Get You a Job in FAANG Companies in 2022
What is a Customer Data Platform and How to Use it?
Top 10 Trending Open-Source Python Projects on GitHub
Enterprise Hybrid AI is the Next Big Thing in Business Ecosystem
Top 10 Enormous Data Science Funding Rounds of 2022 So Far
Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp
_____________
Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.