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Although it would seem straightforward that the laws protecting workers should also apply to workers in what is described as the ‘gig economy’ or ‘platform-based work’, there is much debate – and confusion – on this issue. This lack of clarity stems in part from the novelty of platform-based work. There has also been an effort to conceal the nature of platform-based work through buzzwords such as ‘favours’, ‘rides’, and ‘tasks’ as well as the practice common to many platforms of classifying their workers as independent contractors. Platform-based work includes ‘crowdwork’ and ‘work-on-demand via apps’. In crowdwork, workers complete small jobs or tasks through online platforms, such as Amazon Mechanical Turk, Crowdflower, and Clickworker.  In ‘work-on-demand via apps,’ workers perform duties such as providing transport, cleaning, home repairs, or running errands, but the workers learn about these jobs through mobile apps, from companies such as Uber, Taskrabbit, and Handy. The jobs are performed locally.

Platforms mediate extensively the transactions they have with their workers, and also between the customers and the workers.  Platforms often fix the price of the service as well as define the terms and conditions of the service, or they allow the clients to define the terms (but not the worker). The platform may define the schedule or the details of the work, including instructing workers to wear uniforms, to use specific tools, or to treat customers in a particular way. Many platforms have performance review systems that allow customers to rate the workers and they use these ratings to limit the ability of lower-rated workers to access jobs, including by excluding workers from their system. The amount of direction and discipline that clients and platforms impose on workers, in many instances amounts to the degree of control that is normally reserved to employers and is normally accompanied by labour protections such as the minimum wage, limits on working time, and contributions to social security. This recent ILO study provides more detailed analysis on these features of platform-based work.

For a dollar spent on treatment, up to three are saved in crime reduction. An earlier study found that interventions to address substance use disorders save more in reduced crime than they save in reduced health care spending.

If the history of life on Earth can teach us anything, it is this: as conditions change, species either adapt or become extinct. In our time of considerable environmental change, humanity should consider its options. No species, even the almighty Homo sapiens, can stop evolution completely. But we can choose to limit our capacity for ongoing biological adaptation in an effort to remain ever the same by keeping populations isolated. Of course, such decisions are not made by humanity as a whole but by individuals and governments. Nationalism and xenophobia, on the rise in the US and Europe, threaten to decrease genetic exchange between populations, stifling our ability to continue evolving and adapting.Alternatively, we can embrace immigration and globalisation in an effort to position ourselves for a brighter future.

According to the World Economic Forum’s Future of Jobs report, some jobs will be wiped out, others will be in high demand, but all in all, around 5 million jobs will be lost. The real question is then, how many jobs will be made redundant in the 2020s? Many futurists including Google’s Chief Futurist believe this will necessitate a universal human stipend that could become globally ubiquitous as early as the 2030s.

AI will optimize many of our systems, but also create new jobs. We don’t know the rate at which it will do this. Research firm Gartner further confirms the hypothesis of AI creating more jobs than it replaces, by predicting that in 2020, AI will create 2.3 million new jobs while eliminating 1.8 million traditional jobs.

In an era where it’s being shown we can’t even regulate algorithms, how will we be able to regulate AI and robots that will progressively have a better capacity to self-learn, self-engineer, self-code and self-replicate? This first wave of robots are simply robots capable of performing repetitive tasks, but as human beings become less intelligent trapped in digital immersion, the rate at which robots learn how to learn will exponentially increase.How do humans stay relevant when Big Data enables AI to comb through contextual data as would a supercomputer? Data will no longer be the purvey of human beings, neither medical diagnosis and many other things. To say that AI “augments” human in this respect, is extremely naive and hopelessly optimistic. In many respects, AI completely replaces the need for human beings. This is what I term the automation economy.