Moonshots Challenges

AI and other shifts in the labor force over many decades will probably unleash long-term technology-
enabled changes in the developed countries workforces as they moved most workers from farms to
factories and support occupations. Those shifts did not result in long-term mass unemployment as they
were accompanied by the creation of new types of work not foreseen at the time. We can't definitively
say whether ancient precedent will be repeated this time. But our analysis shows that humans will still
be needed in the workforce.

These include technical feasibility of automation, a critical first step that will rely on sustained breakthrough innovation, but alone isn't sufficient.The price of developing and deploying solutions, labor market dynamics, including demand and supply, and prices of human labor as opposed to automation, business and financial benefits, not only labor substitution benefits, but also benefits from new capabilities that go beyond individual capabilities. Regulatory user and social
acceptance can affect the rate of adoption even when deployment makes business and economic sense.There’s a lot of challenges to overcome before machines can match human performance and cognitive
activity. Among the biggest technical challenges is for machines to obtain the capability to understand
and generate natural language--capabilities that are crucial for a large number of work activities.Work is nothing new (and self-employment is still the predominant form of work in emerging markets),
but the electronic enablement of it is. The percentage of independent work that's conducted on
electronic platforms, although only about 15 percent of independent work overall, is growing rapidly,driven by the scale, efficiency, and ease of use for employees and customers these platforms enable.
We estimate about 25% of CEOs time is currently spent regulating automation. We focused on work
activities as opposed to whole occupations as a starting point. We believe work activities to be a useful
measure since jobs are aggregations of different actions, where each discrete activity has a different
potential for automation.A useful analogy to consider is that of electric vehicles. So even formidable technological challenges
must still be overcome. While independent technologies replace some jobs, they're creating new work
in industries that most of us can't even imagine, in addition to new ways to create income and match
talent to jobs.What about employment and work? The advent of a new automation era is increasing public concerns
about the effect on employment and the future of work. For most occupations, partial automation is
more likely than full automation in the medium term, and the technology will provide new opportunities
for job creation.A few of the gains will come from labor substitution, but automation also has the potential to boost
productivity, raise throughput, improve predictions, outcomes, precision, and optimization, also expand
the discovery of new alternatives in massively complex areas such as synthetic biology and material
science. AI will provide a much-needed boost to global productivity and might help some ‘moonshots challenges. Application of AI and the automation of actions can enable productivity growth and other benefits not just for companies, but also for whole economies.For companies, successful adoption of these evolving technologies will result in job growth and creation of new jobs. New jobs created in the USA in the past 25 years were types that did not previously exist, orhardly existed, in areas such as IT development, hardware production, app creation, and IT systems management. The developing role of large data in the market and business will create a substantial demand for statisticians and data analysts.Technologies can also be broadly beneficial for society by helping handle some “moonshot" challenges, including climate change or curing disease. AI is already being deployed in synthetic biology, cancer research, climate science, and material science. This is one of the exciting outcomes of having a technology such as Dxchain bridging off blockchain tech.Some of these advancements were demonstrated to be technically unfeasible several decades ago, but it wasn't until some of these other variables became realistic that they showed up on your way.

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