With consumer preferences for regained privacy and control, as well as new regulation such as the General Data Protection Regulation (GDPR), it’s plausible to see more data held by the consumer and the consumer exercise more control over where their data is used. Will the new emerging industry for personal assistants & algorithms that empower the consumer and leverage their data for their benefit take over the third-party applications that support consumer behaviour? Who will hold the power in this ecosystem? Will it be the consumer or the algorithm?
Ownership and control may seem removed from how these systems will shape up to be, but I do believe that they are the very core of where interests will lie. Imagine if the algorithm itself has enough power to have a self-interest – meaning, for example, the company that developed it sells it to enough consumers and is primarily driven by adoption in one way or another (to get to monetary transactions, data or both). Would that type of algorithm then optimize for individual representation or the adoption of the actual algorithm itself, where agency theory and agency dilemmas would clearly argue the latter? Even if seemingly innocent (of course, they want to create a business for themselves!), this may be less of a transition from the current internet, where troves of data reside in many forms of companies where users frequent (Amazon, Google, Facebook, etc.).
Now, consider if ownership and control sit with the individual consumers, for example, in the shape or form of individually licensed and tailored software on the consumer’s end-device with full rights to the software. You can even consider a situation where we all get literate enough to produce these algorithms ourselves – the more radical scenario. If “my AI” now literally represents me and is oblivious to all the rest of the consumers with “their AI,” I’ll surely have more power because the system’s incentives and interests will be my own. What I may indeed lose is the centralized, horizontal data benefits and products of scale these algorithms may have if distributed broadly, which would surely be an algorithm developer’s first response why distribution will serve the greater good. Yet, it’s not easy to translate this greater good to something practical or know whom this greater good actually serves.
How could you plausibly get this type of horizontal power as an individual consumer? Could you do so even with remarkable resources at your disposal? And if so, could it be seen as benefiting anyone but yourself?
How about when “my AI” can self-determine where this horizontal benefit may exist and talk not only to “your AI” but to all the “other AIs” in order to get a group discount on a purchase, for example? It may seem far-fetched at the moment, but this type of distributed-node thinking may well be on the horizon sooner than later. Especially, combined with breakthroughs in distributed connectivity and real time processing, we could be at a stage where the power of the network could benefit the individual without a central connectivity.
Decentralized and distributed systems may be the key to unlocking a true network system, where central authority & control are absent and individualism can be discovered through a network. We’d need individual interfaces that are attached to the end-user and a true portability that allows it to interface with the broader network, but it’s hard to imagine that this would not be attainable with current or soon-to-have tools. Maybe this is indeed a future we will soon see, where individual interests will actually be represented rather than those of global corporations.
This post originally appeared on MEDICI.
Internationally awarded digital finance entrepreneur, active in pioneering new securities models worldwide. Has worked in digital finance since 2009, recruited over 100 individuals, built up a operations on six continents and been recognized as one of the top 100 thought leaders in crowdfunding. Markus has pioneered new funding models in the US and Europe, advised policy makers worldwide - including the SEC, the European Commission and Italian regulator CONSOB - for more effective markets, and worked with visionary organizations such as the World Bank and the Kauffman Foundation to improve frameworks for digital finance. Markus has studied computer science and economics (M.Sc).