Law professor Eugene Volokh was apparently the first person to popularize the term cheap speech, in an article for Yale Law Review in 1995.
Recently, Law professor Rick Hasen has been promoting a new book of his own titled Cheap Speech. His definition of cheap speech expands on Volokh’s definition. Quoting directly here from a May 24, 2022 transcript of a Salon interview with Hasen:
Now anybody who has any thought about any New York Times article or about anything else has a free platform. All you have to do is give up your right to privacy and share your data with these companies, and then they’ll let you say whatever you want to, whatever audience you can muster….
…the more outrageous you are, the more likely it is you’re going to attract more eyeballs. And so that creates an incentive to produce more bad speech. And so by cheap speech, Volokh meant just cheap that is inexpensive to produce and disseminate. But I mean it in a way it’s that, but it’s also cheap in that it is of lower value.
Hasen’s specialty is US electoral politics. One key observation he makes is that social and broadcast media influencers amplify the most rage-inducing forms of political dis- and misinformation. The result can be even more polarization of the sentiments of alienated voters of either side of the political spectrum. The network effect, in other words, accelerates the increase in polarization.
Cheap Speech in Data Tech Content
Cheap speech (both spoken word and in the form of text) has also caused distortions on AI and data tech topics, though granted, the distortions are not as dramatic (or as often intentional) as those associated with political topics. The same basic dynamics exist in the datatech trade press as in online media generally –ill-informed, noisy, polar opposite arguments in social and more traditional media draw the most reader attention. Nuanced, informed arguments, meanwhile, get lost in the noise.
For example, worthy use cases for certain “blockchain”-like capabilities exist beyond the realm of cryptocurrency and NFTs. Many organizations have been exploring these use cases. But you might not know that, given the ratio of cheap speech noise that drives investment speculation to insightful, informative signal about quieter efforts.
The consequence of getting lost in the noise is the data purgatory I’ve mentioned in a previous post. Most enterprises ignore or put off the best, long-term, data-centric innovation and the challenging problems such innovation is designed to tackle. It’s not the easiest path to pursue, after all.
Meanwhile, further investment in legacy systems just don’t allow the scope or scale of data integration or decentralized, contextualized identity networking necessary for more substantial AI or digital twin initiatives.
Countering Data Tech Noise
Thoreau published his essay “Civil Disobedience” in 1849. In that essay, Thoreau described the dilemma citizens faced: Government can pass unjust laws or try to compel citizens to do unethical or otherwise irresponsible things against their will. It’s the moral duty of citizens, Thoreau pointed out, to resist this kind of injustice and refuse to be instruments of unjust authority. Thus civil “disobedience” can in some cases be justified.
Citizens face a similar dilemma these days to Thoreau’s, but in the free world, it’s not the power of government or the stated intent of most laws that’s the problem. Instead, here’s what happens that’s problematic on the personal data front:
- Governments pass broad data protection laws such as the Health Insurance Portability and Accountability Act (HIPAA), the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) that can’t be adequately enforced
- Responsible organizations take steps to comply with the stated regulations interpreting the laws
- A few news articles appear about organizations receiving fines for non-compliance
- But the data protection problem, unabated, continues to spiral out of control
Data independence and contrarianism as forms of civil disobedience
A key 21st century civil disobedience obligation in the free online world is to ignore the noise of cheap speech emanating from unenlightened, self-interested media and tech providers. Meanwhile, take control of your own data. Talk to regulators about how their needs and ours overlap, and how compliance could be more effective.
In todays online Wild West, no one else is going to protect the territory you can stake out now. Start to declare your own data homestead and independence, step by step, while doing so is still possible.
Our task is to learn the nature of next-generation data-centric and decentralized identity architecture in the signal to understand what works best and how to support those nascent methods. Events such as the Data-Centric Architecture Forum (DCAF), Solid World and the DID Conference are great places to learn about the overal context of these advances.
Within the frame of a data-centric architecture, initiatives such as Decentralized IDs (DIDs) or personal storage (or SOLID) pods make perfect sense.
The technological means do exist to change circumstances so that you can control more of your data. These technologies need support from technologists to emerge. For example, businesses don’t need users’ correlatable identifiers (government ID numbers for passports, drivers license numbers, mobile phone numbers, email addresses) for authentication.
Instead, data-centric architecture can support self-sovereign identity methods that give users control of the most vulnerable personally identifiable information (PII). The fraction of the data that’s most attractive to thieves can be stored in a hub on your phone and queried via one-time messaging for the authentication, authorization and access control purposes you need to use online services.
Data folks after all, should be among those most likely to understand the dynamics of critical mass theory, which lays out how best to encourage adoption of the most beneficial methods to a tipping point.