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Unintended consequences can be grouped into three types: Unexpected benefit: A positive unexpected benefit (also referred to as luck, serendipity or a windfall). Unexpected drawback: An unexpected detriment occurring in addition to the desired effect of the policy (e.g., while irrigation schemes provide people with water for agriculture, they can increase waterborne diseases that have devastating health effects, such as schistosomiasis). Perverse result: A perverse effect contrary to what was originally intended (when an intended solution makes a problem worse). This is sometimes referred to as 'backfire'.

Robert K. Merton listed five possible causes of unanticipated consequences in 1936:[13] Ignorance, making it impossible to anticipate everything, thereby leading to incomplete analysis Errors in analysis of the problem or following habits that worked in the past but may not apply to the current situation Immediate interests overriding long-term interests Basic values which may require or prohibit certain actions even if the long-term result might be unfavorable (these long-term consequences may eventually cause changes in basic values) Self-defeating prophecy, or, the fear of some consequence which drives people to find solutions before the problem occurs, thus the non-occurrence of the problem is not anticipated

The unemployment rate is at a 17-year low, but stagnant wages, chronic underemployment and growing inequality are leading more Americans to take on so-called side hustles. Some want to supplement their incomes. Others are just trying to eke out a living. Nearly 1 in 4 Americans now earn money from the digital “platform economy,” according to the Pew Research Center. Most of that work is for domestic tasks, such as housecleaning and repairs, or driving for companies such as Uber.

But labor experts say companies such as Snag Work could set a dangerous precedent. Employers are already wary of hiring full-time employees because of overtime and health-care costs, they say, and having a pool of potential gig workers at the ready could make matters worse for those seeking the stability, benefits and protections that come with full-time work.

The rise of artificial intelligence is forcing us to take abstract ethical dilemmas much more seriously because we need to code in moral principles concretely. Should a self-driving car risk killing its passenger to save a pedestrian? To what extent should a drone take into account the risk of collateral damage when killing a terrorist? Should robots make life-or-death decisions about humans at all? We will have to make concrete decisions about what we will leave up to humans and what we will encode into software.