Negative innovation causes societal harms- hurts democracy, health disinformation, economic risks, and exacerbates algorithmic bias.

6. Societal Harms. Innovations sometimes do more than harm individuals or competitors; they damage society itself. We enumerate this category to capture a wide variety of antisocial outcomes that are more generalized than the particularized harms described above. We focus on three issues: risks to democracy, risks to the financial system, and distributive harms. Each of these issues is hugely important, and we can do no more than scratch the surface of any one of them in this Article.

The risks that social media poses to democratic values are becoming increasingly apparent. In addition to its addictive qualities, which hurt many users, social media is a conduit for dangerous misinformation and conspiracy theories.304 Russian operatives have repeatedly used social media to spread propaganda designed to undermine free and fair elections in the United States and other democracies.305 Compelling evidence exists that in both 2016 and 2020, Russia used Facebook and other social media outlets to support the Trump campaign and to sow division among Americans.306 In a post-mortem on the 2016 election, the Senate Intelligence Committee, then led by Republicans, concluded that Russia’s social media strategy “was overtly and almost invariably supportive of then-candidate Trump.”307 Committee Chairman Senator Richard Burr explained that Russia “flood[ed] social media with false reports, conspiracy theories, and trolls” to “exploit[] existing divisions” in U.S. society and “breed distrust of our democratic institutions and our fellow Americans.”308

Social media is easy to weaponize. It is an open system that reaches billions of users worldwide. Anyone can post anything on these sites, and while Twitter (now “X”), Facebook, and other social media outlets employ content moderation teams to various extents to try to limit damaging misinformation, so far these efforts have proved ineffective (and some would say half-hearted).309 Not surprisingly, these platforms have been used not only by state actors like Russia, and not just to threaten democracy, but also by non-state actors with a variety of antisocial goals like undermining public health through anti-vaccine disinformation and stoking racial division.310

Innovation in the financial sector is another common source of social harm. Some financial innovations threaten the nation’s systemic stability. Credit default swaps (CDS) are an example. These instruments, created in the 1990s, were initially developed as a tool for institutions and firms to hedge credit risk. 311 A firm that had made a large loan could use a CDS to take out insurance against a default. The lender would pay premiums to another institution for a guarantee that it would cover any losses if the borrower defaulted on the loan. In this form, CDS could be seen as potentially prosocial because they allow for spreading credit risk, thereby increasing the flow of capital.312

In the run-up to the 2008 financial crisis, however, CDS developed into a means for rampant, unregulated speculation.313 Instead of being used only to hedge lenders’ risks, financial institutions offered CDS to third parties that wanted to bet that specific firms or specific financial instruments would fail.314 Many of these CDS were taken out against mortgage-backed securities that became worthless when the housing market crashed in 2007.315 The firms that had guaranteed payouts if these instruments failed were overwhelmed and the financial system reached the brink of disaster before the federal government stepped in. American International Group (AIG), which had been the largest insurance company in the world, held many of these CDS contracts through a subsidiary, and had to be rescued by the government.316 While CDS did not cause the financial crisis, they worsened it, and the costs of cleaning up the mess were borne by taxpayers.317

High-frequency trading is another financial innovation that causes social harm. In certain financial markets fractions of a second make a difference for investors’ profits, so some trading firms invest heavily in technology that shaves milliseconds off their trading speeds.318 Studies have shown that these advances in speed reduce liquidity in affected markets, raising the costs for other investors.319 High-frequency trading is yet another example of a clear product improvement making conditions worse for innocent third parties, in this case by distorting financial markets. Finally, but of enormous importance, is the effect that innovations may have on the distribution of scarce resources in society. Thinking about distributional harms is challenging because many canonically valuable innovations nonetheless cause distributive harm. For example, the introduction of electric lamps in households and workplaces caused a revolution in society’s health and well-being.320 But electric lamps were terrible for whalers and kerosene salesman whose oil sales were displaced.321 Again, this is the sort of creative destruction that is appropriately lauded by innovation scholars.

In other cases, the normative desirability of an innovation’s distributive consequences may be much less clear. Innovations almost always create both winners and losers, so the distributive consequences depend on these parties’ identities. On one hand, consider the winners. Electrification’s winners were enormously widespread. After its introduction around 1900, electricity reached 80% of the American population by 1940.322 The winners other innovations create are likely to be less numerous and less well distributed throughout the community. For example, the benefits of financial innovations largely redound to a small class of already wealthy traders and investors.323 The same is true for pricing algorithms that function to transfer wealth from the great mass of consumers to a smaller class of producers.324

Now, on the other hand, consider innovation’s losers. The increasing use of algorithms to determine much of our social, work, and political lives may turn out to be net beneficial in the long run, but—at least so far—these technologies may generate exaggerated biases against women, people of color, and people with disabilities, among others.325 Sometimes this means that socially marginalized groups suffer representational biases at the hands of algorithmic innovations, but they also suffer allocative and interpersonal harms as well.326 For example, in the employment context, algorithms may give preferences to men, or they may match Black applicants predominantly with Black-owned businesses.327

In cases such as these, where an innovation’s benefits to men, white people, rich people, or people from the global north technically exceed the innovation’s costs to marginalized people, we might still characterize the innovation as antisocial and worthy of regulation. Our goal here is not to defend a particular calculus for trading off welfare versus distributional concerns but merely to point out that there are a host of innovations that appear prosocial if viewed from the perspective of net welfare that may turn out to be antisocial when their distributional impacts are considered.