Tuesday, January 14, 2025

Original Branding

 This vision of social media future is meant to complement and clarify the vision behind many of my other works (such as this, see list of selected pieces at the end). It assumes you have come here after seeing at least one of those (but includes enough background to also be read first).

Business opportunity – start now, and grow from there:

     Managers of the NY Times, small local news services, or any other organization that has built a strong community can use the following model to build a basic online middleware service business, starting now.

     For example, Bluesky could be a base platform for building initial proof-of-concept services along these lines that could develop and grow into a major business.

[If you are impatient, jump to the section on "Branding"]

It is clear that social media technology is not serving social values well. But it is not so clear how to do better. I have been suggesting that the answer begins in learning from how we, as a society, curated information flows offline. (These issues are also increasingly relevant to emerging AI.)

This piece envisions how an offline curation “brand” with an established following – like the New York Times, or many others, including non-commercial communities of all kinds – could extend their curatorial influence, and the role of their larger community, more deeply into the digital future of thought. (Of course, much the same kind of service can be built as a greenfield startup, as well, but having an established community reduces the cold-start problem.)

Building on middleware – the Three Pillars

I and many others have advocated for “middleware” services, a layer of enabling technology that sits between users and platforms to give control back to users over what goes into each of our individual feeds. But that is just the start of how that increased user agency can support healthy discourse and limit fragmentation and polarization in our globally online world.

 The pillars I have been writing about are:

  1. Individual agency
    , the starting point of democratic free choice over what we say to whom, what individuals we listen to, and what groups we participate in.
  2. Social mediation, the social processes, enabled by an ecosystem of communities and institutions of all kinds that influence and propagate our thoughts, expression, and impression. (For simple background, see What Is a Social Mediation Ecosystem?)
  3. Reputation, the quality metrics, intuitively developed and shared to decide which individuals and communities are trustworthy, and thus deserve our attention (or our skepticism).

Middleware can sit on top of our basic social networking platforms to support the synergistic operation of all three pillars, and thus help make our discourse productive.

In the offline world of open societies, there is no single source of “middleware” services that guide us, but an open, organic, and constantly adjusted mix of many sources of collective support. People grow up learning intuitively to develop and apply these pillars in ever-changing combinations.

Software is far more rigid than humans. Online middleware is a technique for enabling the same kind of diversity and “interoperation” – of attention agent services for us to choose from, and to help groups fully participate in them – so we can dynamically compose the view of the world we want at any point in time.

Bluesky currently offers perhaps the best hint at how middleware services will be composed, steered, and focused – as our desires, tasks, and moods change. Just keep in mind that current middleware offerings are still just infants learning to crawl.

As we may think …together

Vannevar Bush provided a prescient vision of the web in 1945 (yes, 1945!) – in his Atlantic article “As We May Think.” Its technology was quaint, but the vision of how humans can use machines to help us think was very on-point, and inspired the creation of the web. Now it is time for a next level vision – of how we may think together – even if the details of that vision are still crude.

Current notions of middleware have been focused primarily on user agency, and just beginning (as in Bluesky) to consider how we need not just a choice of a single middleware agent service, but to flexibly compose and steer among many attention agent services. Steve Jobs spoke of computers as “bicycles for our minds.” As we conduct our discourse, middleware-based attention agent services can give us handlebars to steer them and gear shifts to deal with varying terrain and motivations. They can give us “lenses,” for focusing what we see from our bicycles.

To build out this capability, we will need at least two levels of user-facing middleware services:

     Many low level service agents that curate for specific objectives of subject domain, styles, moods, sources, values, and other criteria.

     One or more high level service agents that make it easy to orchestrate those low level agents, as we steer them, shift gears, and change our focus, creating a consolidated ranking that gives us what we want, and screens out what we do not want, at any given time.

Just how those will work will change greatly over time as we learn to drive these bicycles, and providers learn to supply useful services – “we shape our tools and our tools shape us.” Emerging AI in these agents will increase the ease of use, and the usable power of the bicycles – but even in the age of AI, the primary intelligence and judgment must come from the humans that use these systems and create the terrain of existing and new information and ideas (not just mechanically reassembled tokens of existing data) that we steer through.

====================================================
Here is the business opportunity:
====================================================

Branding – a “handle” for intuitively easy selection  -- and signaling value

Yes, choosing middleware services seems complicated, and skeptics rightly observe that most users lack the skill or patience to think very hard about how to steer these new bicycles for our minds. But there are ways to make this easy enough. One of the most promising and suggestive is branding – a powerful and user-friendly tool for reliably selecting a service to give desired results. Take the important case of news services:

     If we try to select news stories at the low level of all the different dimensions of choice – subject matter, style, values, and the like – of course the task would be very complex and burdensome.

     But many millions easily choose what mix of CNN, MSNBC, Fox News, PBS, or less widely used brands they want to watch at any time. The existing brand equity and curation capabilities of such media enterprises are now being squandered by digital platforms that offer such established service brands only rudimentary integration into their social media curation processes. With proper support, both established and new branded middleware services can establish distinctive sensibilities that can make choice easy.

Importantly, branding also serves marketing and revenue functions in powerful ways that can be exploited by middleware services. Once established and nurtured, a brand attracts users on the basis that it offers known levels of quality, and as catering to selective interests and tastes. "It's Not TV, It's HBO" encapsulated the power of HBO's brand in the heyday of premium TV.

The New York Times as a branded curation community: 

Consider the New York Times as just one example of branded curation middleware that could serve as a steerable lens into global online discourse. It could just as well be News Corp, CNN, Sports Illustrated, or Vogue – or your local newspaper (if you still have one!) – or your town or faith community, a school, a civil society organization, a political party, a library, a bowling league – or whatever group or institution that wants to support its uniquely focused (but overlapping and not isolated) segment of the total social mediation ecosystem.

Consider how all three pillars can work and synergize in such a service:

User agency comes in by our participation as readers, and as speakers in any relevant mode – posts, comments, likes, shares, letters to the editor, submissions for Times publications. This can be addressed at at least two levels:

     Low level attention service agents that find and rank candidate items for our feeds and recommenders. This is much as we now choose from an extensive list of available email newsletters from the Times.

     Higher level middleware composing agents would help compose these low-level choices – and facilitate interoperation with similar services from other communities – to build a composite feed of items from the Times and all our other chosen sources. They could offer sliders to decide what mx to steer into a feed at any given time, and saved presets to shift gears for various moods, such as news awareness/analysis, sports/entertainment, challenging ideas, light mind expansion, and diversion/relaxation.

(Different revenue models may apply to different services, levels, and modes of participation, just as some NY Times features now may cost extra.)

Social mediation processes come in to our user interface at two levels of curation:

     User-driven curation: Much like current platforms, the Times low-level services can rank items based on signals from the community of Times users – their likes, shares, comments, and other signals of interest and value. This might distinguish subscribers versus non-subscribing readers. Subscribers might be more representative of the community, but non-subscribers might bring important counterpoints. Other categories could include special users, such as public figures in various political, business, or professional categories. As such services mature, these signals can be expanded in variety to be far more richly nuanced, such as to give clearer feedback and be categorized by subject domains of primary involvement. 

     Expert-driven curation: The Times editorial team can be drawn on (and potentially augmented with supportive levels of AI) to provide high quality expert curation services in much the same way, in whatever mix desired. This could include both their own contributions, and their reactions to readers’ contributions.

Reputation systems that keep score of quality and trust feedback on both users and content items – that arise from those mediation processes – can also be valuably focused on the Times community:

     At a gross level, we might make gross assumptions that differentiate the editorial and journalism staff, subscribers, and non-subscribing readers (as part of the basic mediation process), but a reputation system could distinguish among very different levels of reputation for quality of participation in many dimensions, such as expertise, judgment, clarity, wisdom, civility, and many more – in each of many subject domains.

     Reputation systems might also be tuned to Times reporters and editors, and their inputs to reputations of content items and users. But the true power of this kind of service is its crowdsourcing from not just the Times staff, but from its unique extended community. One could choose to ignore the staff, and just turn their lens on the community, or vice versa.

Enterprise-class community support integration – and simple beginnings

To fully enable this would require new operational support services that integrate the operation of open online social media platform services (like Bluesky now, or maybe someday Threads) with the operations of the Times. As the technology for multi-group participation is built out beyond current rudimentary levels, it can integrate with the operation of each group, including the enterprise-class systems that drive the operations of the Times. This might include the kind of functionality and integration offered by CRM (customer relationship management) systems for managing all of the Times’ interactions with its customers, as well as the CMS (content management system) used to manage its journalism content, and the SMS (subscription management systems) that manage revenue operations.

Doing all of this fully will take time and effort – but some of it could be done relatively easily, such as in an attention agent that ranks items based on the Times community members signals as distinct from those of the general network population. The Times could begin a trial of this in the near term by exploiting the basic middleware capabilities already available by creating a Bluesky server instance (using the open Bluesky server code and interoperation protocols) and their own custom algorithms. 

A large, profitable (or otherwise well-funded) business like the Times could develop and operate middleware software itself (if the social media platform allows that, as Bluesky does), but smaller organizations might need a shared “middleware as a service” (MaaS) software and operations provider to do much of that work.

A user steered, intuitively blended, mix of diverse sub-community feeds

Even at a basic level, imagine how doing this for many such branded ecosystem groups could enable users to easily compose feeds that bring them a diverse mix of quality inputs, and to steer and adjust the lenses in those feeds and searches to focus our view as we desire, when we desire.

Similar middleware services could be based all kinds of groups – for example:

     Local news and community information services – much like the Times example, for where you live now, used to live, or want to live or visit.

     Leadership and/or supporters of political parties or civil society organizations – issues, platforms/policies, campaigns, turnout, surveys, fact-checking, and volunteering.

     Professional and/or amateur players and/or coaches for sports – catering to teams, fans, sports lore, and fantasy leagues.

     Faculty, students, and/or alumni from universities – selecting for students, faculty, alumni, applicants, parents.

     Librarians and/or card holders for library systems – selecting for discovery, reading circles, research, criticism, and authors.

     Leaders and/or adherents to faith communities – for community news, personal spiritual issues, and social issues.

Consider how the Times example translates to and complements any of these other kinds of groups (most easily if enabling software is made available from a SaaS provider). Users could easily orchestrate their control over diverse sources of curation and moderation – selecting from brands with identities they recognize – without requiring the prohibitive cognitive load of controlling all the details that critics now argue would doom middleware because few would bother to make selections. New brands can also emerge and gain critical mass, using this same technology base.

By drawing on signals from expert and/or ordinary members of groups that have known orientations and norms, users might easily select mixes that serve their needs and values – and shift them as often as desired.

Context augmentation

Peter Steiner in The New Yorker

"On the Internet, no one knows you are a dog" -- or a lunatic, or a bot. Famously observed by Peter Steiner's 1993 cartoon, this became known as "context collapse," broadly understood as a core reason why internet discourse is so problematic. Much of the meaning derives from context external to the message itself -- who is speaking to whom, from and to what community, with what norms and assumptions. That has largely been lost in current social media (and in emerging AIs). 

Consider how the kind of social mediation ecosystem processes envisioned here differ from what current major platforms offer in the way of community support -- and thus fail to provide essential context: 

  • They let you create a personal set (a unidirectional pseudo-community) of friends or those you follow, but increasingly focus on engagement-based ranking into feeds -- because they want to maximize advertising revenue, not the quality of your experience. 
  • They rank based on likes, shares, and comments from a largely undifferentiated global audience, with little opportunity for you to influence who is included. 
  • They may favor feedback from rudimentary "groups" that you join, but provide very limited support to organizers and members to make those groups rich and cohesive. 
  • They may cluster you into what they infer to be your communities of interest, but with out any agency from you over which groups those are, except for the rudimentary "groups" you join.
  • And, even if they did want to serve your objectives, not theirs, they would be hard-pressed to come anywhere near the richness and diversity of truly independent, opt-in, community-driven middleware services that are tailored to diverse needs, contexts, and sustaining revenue models.

Doing moderation the old-fashioned way – enabled by middleware

Instead of being seen as a magical leap in technology, or an off-putting cognitive burden on users, middleware can be understood as a way to recreate in digital form the formal and informal social structures people have enjoyed for centuries – individually composed interaction with the wisdom of organically evolved social mediation ecosystems and intuitive informal reputation systems.

What at first seems complicated, from the perspective of current social media, is at core, little more complicated than the structure of traditional human discourse – building on key functions and elements of the social mediation and reputation ecosystems – all legitimized by choices of individual agency. Yes, that is complicated, but humans have learned over millennia to intuitively navigate this traditional web of communities and reputations. Yes, make it as simple as possible, but no simpler!

Creating an online twin of such a web of community ecosystems will not happen overnight, but many industries have already built out online infrastructures of similar complexity – in finance, manufacturing, logistics, travel, and e-commerce. Middleware is just a tool for enabling software systems to work together in ways similar to what humans (and groups of humans) do intuitively. The time to start rebuilding those ecosystems is now.

____________________

Related works:

     My November 2023 post introducing the pillars framing – A New, Broader, More Fundamental Case for Social Media Agent "Middleware" – introduced the Three Pillars framing, and embeds a deck that adds details and implication not yet fully addressed elsewhere.

     Core ideas addressed more formally in my April 2024 CIGI policy brief, New Logics for Governing Human Discourse in the Online Era.

     Very simply -- What Is a Social Mediation Ecosystem? (and Why We Need to Rebuild It). 

     Other related works are listed on my blog.



Jump link Tag test

This vision of social media future is meant to complement and clarify the vision behind many of my other works (such as this, see list of selected pieces at the end). It assumes you have come here after seeing at least one of those (but includes enough background to also be read first).

Business opportunity – start now, and grow from there:

     Managers of the NY Times, small local news services, or any other organization that has built a strong community can use the following model to build a basic online middleware service business, starting now.

     For example, Bluesky could be a base platform for building initial proof-of-concept services along these lines that could develop and grow into a major business.

[If you are impatient, jump to the section on "Branding"]

It is clear that social media technology is not serving social values well. But it is not so clear how to do better. I have been suggesting that the answer begins in learning from how we, as a society, curated information flows offline. (These issues are also increasingly relevant to emerging AI.)

This piece envisions how an offline curation “brand” with an established following – like the New York Times, or many others, including non-commercial communities of all kinds – could extend their curatorial influence, and the role of their larger community, more deeply into the digital future of thought. (Of course, much the same kind of service can be built as a greenfield startup, as well, but having an established community reduces the cold-start problem.)

Building on middleware – the Three Pillars

I and many others have advocated for “middleware” services, a layer of enabling technology that sits between users and platforms to give control back to users over what goes into each of our individual feeds. But that is just the start of how that increased user agency can support healthy discourse and limit fragmentation and polarization in our globally online world.

 The pillars I have been writing about are:

  1. Individual agency
    , the starting point of democratic free choice over what we say to whom, what individuals we listen to, and what groups we participate in.
  2. Social mediation, the social processes, enabled by an ecosystem of communities and institutions of all kinds that influence and propagate our thoughts, expression, and impression. (For simple background, see What Is a Social Mediation Ecosystem?)
  3. Reputation, the quality metrics, intuitively developed and shared to decide which individuals and communities are trustworthy, and thus deserve our attention (or our skepticism).

Middleware can sit on top of our basic social networking platforms to support the synergistic operation of all three pillars, and thus help make our discourse productive.

In the offline world of open societies, there is no single source of “middleware” services that guide us, but an open, organic, and constantly adjusted mix of many sources of collective support. People grow up learning intuitively to develop and apply these pillars in ever-changing combinations.

Software is far more rigid than humans. Online middleware is a technique for enabling the same kind of diversity and “interoperation” – of attention agent services for us to choose from, and to help groups fully participate in them – so we can dynamically compose the view of the world we want at any point in time.

Bluesky currently offers perhaps the best hint at how middleware services will be composed, steered, and focused – as our desires, tasks, and moods change. Just keep in mind that current middleware offerings are still just infants learning to crawl.

As we may think …together

Vannevar Bush provided a prescient vision of the web in 1945 (yes, 1945!) – in his Atlantic article “As We May Think.” Its technology was quaint, but the vision of how humans can use machines to help us think was very on-point, and inspired the creation of the web. Now it is time for a next level vision – of how we may think together – even if the details of that vision are still crude.

Current notions of middleware have been focused primarily on user agency, and just beginning (as in Bluesky) to consider how we need not just a choice of a single middleware agent service, but to flexibly compose and steer among many attention agent services. Steve Jobs spoke of computers as “bicycles for our minds.” As we conduct our discourse, middleware-based attention agent services can give us handlebars to steer them and gear shifts to deal with varying terrain and motivations. They can give us “lenses,” for focusing what we see from our bicycles.

To build out this capability, we will need at least two levels of user-facing middleware services:

     Many low level service agents that curate for specific objectives of subject domain, styles, moods, sources, values, and other criteria.

     One or more high level service agents that make it easy to orchestrate those low level agents, as we steer them, shift gears, and change our focus, creating a consolidated ranking that gives us what we want, and screens out what we do not want, at any given time.

Just how those will work will change greatly over time as we learn to drive these bicycles, and providers learn to supply useful services – “we shape our tools and our tools shape us.” Emerging AI in these agents will increase the ease of use, and the usable power of the bicycles – but even in the age of AI, the primary intelligence and judgment must come from the humans that use these systems and create the terrain of existing and new information and ideas (not just mechanically reassembled tokens of existing data) that we steer through.

====================================================
Here is the business opportunity:
====================================================

Branding – a “handle” for intuitively easy selection  -- and signaling value

Yes, choosing middleware services seems complicated, and skeptics rightly observe that most users lack the skill or patience to think very hard about how to steer these new bicycles for our minds. But there are ways to make this easy enough. One of the most promising and suggestive is branding – a powerful and user-friendly tool for reliably selecting a service to give desired results. Take the important case of news services:

     If we try to select news stories at the low level of all the different dimensions of choice – subject matter, style, values, and the like – of course the task would be very complex and burdensome.

     But many millions easily choose what mix of CNN, MSNBC, Fox News, PBS, or less widely used brands they want to watch at any time. The existing brand equity and curation capabilities of such media enterprises are now being squandered by digital platforms that offer such established service brands only rudimentary integration into their social media curation processes. With proper support, both established and new branded middleware services can establish distinctive sensibilities that can make choice easy.

Importantly, branding also serves marketing and revenue functions in powerful ways that can be exploited by middleware services. Once established and nurtured, a brand attracts users on the basis that it offers known levels of quality, and as catering to selective interests and tastes. "It's Not TV, It's HBO" encapsulated the power of HBO's brand in the heyday of premium TV.

The New York Times as a branded curation community: 

Consider the New York Times as just one example of branded curation middleware that could serve as a steerable lens into global online discourse. It could just as well be News Corp, CNN, Sports Illustrated, or Vogue – or your local newspaper (if you still have one!) – or your town or faith community, a school, a civil society organization, a political party, a library, a bowling league – or whatever group or institution that wants to support its uniquely focused (but overlapping and not isolated) segment of the total social mediation ecosystem.

Consider how all three pillars can work and synergize in such a service:

User agency comes in by our participation as readers, and as speakers in any relevant mode – posts, comments, likes, shares, letters to the editor, submissions for Times publications. This can be addressed at at least two levels:

     Low level attention service agents that find and rank candidate items for our feeds and recommenders. This is much as we now choose from an extensive list of available email newsletters from the Times.

     Higher level middleware composing agents would help compose these low-level choices – and facilitate interoperation with similar services from other communities – to build a composite feed of items from the Times and all our other chosen sources. They could offer sliders to decide what mx to steer into a feed at any given time, and saved presets to shift gears for various moods, such as news awareness/analysis, sports/entertainment, challenging ideas, light mind expansion, and diversion/relaxation.

(Different revenue models may apply to different services, levels, and modes of participation, just as some NY Times features now may cost extra.)

Social mediation processes come in to our user interface at two levels of curation:

     User-driven curation: Much like current platforms, the Times low-level services can rank items based on signals from the community of Times users – their likes, shares, comments, and other signals of interest and value. This might distinguish subscribers versus non-subscribing readers. Subscribers might be more representative of the community, but non-subscribers might bring important counterpoints. Other categories could include special users, such as public figures in various political, business, or professional categories. As such services mature, these signals can be expanded in variety to be far more richly nuanced, such as to give clearer feedback and be categorized by subject domains of primary involvement. 

     Expert-driven curation: The Times editorial team can be drawn on (and potentially augmented with supportive levels of AI) to provide high quality expert curation services in much the same way, in whatever mix desired. This could include both their own contributions, and their reactions to readers’ contributions.

Reputation systems that keep score of quality and trust feedback on both users and content items – that arise from those mediation processes – can also be valuably focused on the Times community:

     At a gross level, we might make gross assumptions that differentiate the editorial and journalism staff, subscribers, and non-subscribing readers (as part of the basic mediation process), but a reputation system could distinguish among very different levels of reputation for quality of participation in many dimensions, such as expertise, judgment, clarity, wisdom, civility, and many more – in each of many subject domains.

     Reputation systems might also be tuned to Times reporters and editors, and their inputs to reputations of content items and users. But the true power of this kind of service is its crowdsourcing from not just the Times staff, but from its unique extended community. One could choose to ignore the staff, and just turn their lens on the community, or vice versa.

Enterprise-class community support integration – and simple beginnings

To fully enable this would require new operational support services that integrate the operation of open online social media platform services (like Bluesky now, or maybe someday Threads) with the operations of the Times. As the technology for multi-group participation is built out beyond current rudimentary levels, it can integrate with the operation of each group, including the enterprise-class systems that drive the operations of the Times. This might include the kind of functionality and integration offered by CRM (customer relationship management) systems for managing all of the Times’ interactions with its customers, as well as the CMS (content management system) used to manage its journalism content, and the SMS (subscription management systems) that manage revenue operations.

Doing all of this fully will take time and effort – but some of it could be done relatively easily, such as in an attention agent that ranks items based on the Times community members signals as distinct from those of the general network population. The Times could begin a trial of this in the near term by exploiting the basic middleware capabilities already available by creating a Bluesky server instance (using the open Bluesky server code and interoperation protocols) and their own custom algorithms. 

A large, profitable (or otherwise well-funded) business like the Times could develop and operate middleware software itself (if the social media platform allows that, as Bluesky does), but smaller organizations might need a shared “middleware as a service” (MaaS) software and operations provider to do much of that work.

A user steered, intuitively blended, mix of diverse sub-community feeds

Even at a basic level, imagine how doing this for many such branded ecosystem groups could enable users to easily compose feeds that bring them a diverse mix of quality inputs, and to steer and adjust the lenses in those feeds and searches to focus our view as we desire, when we desire.

Similar middleware services could be based all kinds of groups – for example:

     Local news and community information services – much like the Times example, for where you live now, used to live, or want to live or visit.

     Leadership and/or supporters of political parties or civil society organizations – issues, platforms/policies, campaigns, turnout, surveys, fact-checking, and volunteering.

     Professional and/or amateur players and/or coaches for sports – catering to teams, fans, sports lore, and fantasy leagues.

     Faculty, students, and/or alumni from universities – selecting for students, faculty, alumni, applicants, parents.

     Librarians and/or card holders for library systems – selecting for discovery, reading circles, research, criticism, and authors.

     Leaders and/or adherents to faith communities – for community news, personal spiritual issues, and social issues.

Consider how the Times example translates to and complements any of these other kinds of groups (most easily if enabling software is made available from a SaaS provider). Users could easily orchestrate their control over diverse sources of curation and moderation – selecting from brands with identities they recognize – without requiring the prohibitive cognitive load of controlling all the details that critics now argue would doom middleware because few would bother to make selections. New brands can also emerge and gain critical mass, using this same technology base.

By drawing on signals from expert and/or ordinary members of groups that have known orientations and norms, users might easily select mixes that serve their needs and values – and shift them as often as desired.

Context augmentation

Peter Steiner in The New Yorker

"On the Internet, no one knows you are a dog" -- or a lunatic, or a bot. Famously observed by Peter Steiner's 1993 cartoon, this became known as "context collapse," broadly understood as a core reason why internet discourse is so problematic. Much of the meaning derives from context external to the message itself -- who is speaking to whom, from and to what community, with what norms and assumptions. That has largely been lost in current social media (and in emerging AIs). 

Consider how the kind of social mediation ecosystem processes envisioned here differ from what current major platforms offer in the way of community support -- and thus fail to provide essential context: 

  • They let you create a personal set (a unidirectional pseudo-community) of friends or those you follow, but increasingly focus on engagement-based ranking into feeds -- because they want to maximize advertising revenue, not the quality of your experience. 
  • They rank based on likes, shares, and comments from a largely undifferentiated global audience, with little opportunity for you to influence who is included. 
  • They may favor feedback from rudimentary "groups" that you join, but provide very limited support to organizers and members to make those groups rich and cohesive. 
  • They may cluster you into what they infer to be your communities of interest, but with out any agency from you over which groups those are, except for the rudimentary "groups" you join.
  • And, even if they did want to serve your objectives, not theirs, they would be hard-pressed to come anywhere near the richness and diversity of truly independent, opt-in, community-driven middleware services that are tailored to diverse needs, contexts, and sustaining revenue models.

Doing moderation the old-fashioned way – enabled by middleware

Instead of being seen as a magical leap in technology, or an off-putting cognitive burden on users, middleware can be understood as a way to recreate in digital form the formal and informal social structures people have enjoyed for centuries – individually composed interaction with the wisdom of organically evolved social mediation ecosystems and intuitive informal reputation systems.

What at first seems complicated, from the perspective of current social media, is at core, little more complicated than the structure of traditional human discourse – building on key functions and elements of the social mediation and reputation ecosystems – all legitimized by choices of individual agency. Yes, that is complicated, but humans have learned over millennia to intuitively navigate this traditional web of communities and reputations. Yes, make it as simple as possible, but no simpler!

Creating an online twin of such a web of community ecosystems will not happen overnight, but many industries have already built out online infrastructures of similar complexity – in finance, manufacturing, logistics, travel, and e-commerce. Middleware is just a tool for enabling software systems to work together in ways similar to what humans (and groups of humans) do intuitively. The time to start rebuilding those ecosystems is now.

____________________

Related works:

     My November 2023 post introducing the pillars framing – A New, Broader, More Fundamental Case for Social Media Agent "Middleware" – introduced the Three Pillars framing, and embeds a deck that adds details and implication not yet fully addressed elsewhere.

     Core ideas addressed more formally in my April 2024 CIGI policy brief, New Logics for Governing Human Discourse in the Online Era.

     Very simply -- What Is a Social Mediation Ecosystem? (and Why We Need to Rebuild It). 

     Other related works are listed on my blog.



Wednesday, January 8, 2025

Beyond the Pendulum Swings of Centralized Moderation (X/Twitter, Meta, and Fact Checking)

 The crazy pendulum swings of centralized moderation by dominant social media platforms is all over the news again, as nicely summarized by Will Oremus, and explored by a stellar Lawfare panel of experts. 

We have seen a swing toward what many perceive as blunt over-moderation and censorship in 2016-17, and now a swing away, to what others view as irresponsibly enabling uncontrolled cesspools of anger, hate, and worse. This pendulum is clearly driven in large part by the political winds (which it influences, in turn), a question of whose ox gets gored, and who has the power to influence the platforms -- "Free speech for me, but not for thee."

This will remain a crazy pendulum -- and one that can destroy the human community and its collective intelligence -- until we step back and take a smarter approach to context and diversity of our perceptions of speech. Shifting toward community moderation, as X/Twitter and Meta/Facebook/Threads are now doing, may point in the right direction: to democratize that control -- but is done with only a minimal and flawed hint of real democracy. Even if they really try, centralized platforms are inherently incapable of  doing that well. Here are some quick notes on why, and how to do better.

Three of the speakers on the Lawfare panel were coauthors/contributors with me in a comprehensive white paper, based on a symposium on a partially decentralized approach called "middleware." That proposes an open market in independent curation and moderation services that sit in the middle between the user and the platforms. These services can do community-based moderation is a full range of ways, at a community level, much more like the way traditional communities have always done "moderation" (better thought of as "mediation") of how we communicate with others. This new middleware paper explains the basics, why it is a promising solution, and how to make it happen. (For a real-world example of middleware, but still in its infancy, consider Bluesky.)

As for the current platform approach to "community moderation," many have critiqued it, but I suggest a deeper way to think about this, more in line with how humans have always mediated their speech. Three Pillars of Human Discourse (and How Social Media Middleware Can Support All Three is a recent piece on extending current ideas on middleware to support this solution that has evolved over centuries of human society.

Specific to community moderation

The Augmented Wisdom of Crowds: Rate the Raters and Weight the Ratings (from 2018) digs deeper into why simplistic attempts at community surveys fail, and how the same kind of advanced analysis of human inputs that made Google win the search engine wars can be applied to social media. A 2021 post updates that.

To understand why this is important, consider what I call The Zagat Olive Garden Problem. In the early 90s, I noticed this in the popular community-rating service Zagat published on restaurants: The top 10 or so restaurants in NYC were almost all high-priced, haute cuisine or comparably refined, but one was Olive Garden. Because Olive Garden food was just as good? No, because far more people knew it from their many locations, and far more were attracted to a familiar brand with reasonably tasty food at modest prices. 

Doing surveys where all votes are counted equally sounds democratic, but is foolishly so. We really want ratings from those with a reputation for tastes we relate to and trust -- but leavened with healthy diversity on how we should broaden our horizons. That is what good feed and recommender algorithms can do. We need to "rate the raters and weight the ratings."

Back to the pendulum model, consider how pendulums work -- especially the phenomenon of entrainment. Glossing over many details...

  • Back in 1666, Huygens invented the pendulum clock and discovered that if two were mounted on the same wall, their pendulum swings gradually became synchronized. That is because each interacts with the shared wall to exchange energy in a way that brings them into phase.
  • Simplistically, moderation is a pendulum that can swing from false positives to false negatives. Each platform has one big pendulum controlled by one person/corporation that swings with the political wind (or other platform influences). Platform-level community moderation entrains everyone to that one pendulum, whether it fits or not -- many false positives and false negatives, often biased one way or the other.
  • A distributed system of middleware services can serve many individuals or communities, each with their own pendulums that swing to their own tastes.
  • Within communities, these pendulums are linked (the shared wall) and tend to entrain.
  • Across communities, there are also weaker linkages, in different dimensions, so still a nudge toward entrainment.
  • In addition to these linkages in many dimensions, instead of being rigid, the walls of human connection are somewhat elastic in how they entrain.
  • The Google PageRank algorithm is based on advanced math (eigenvalues) that treats individual search engine users as clustering into diverse communities of interest and value -- much like a network of pendulums all linked to one another by elastic "walls" in a multidimensional array.
  • Similar algorithms can be used by diverse middleware services to distill community ratings with the same nuanced sensitivity to their diverse community contexts. Not perfectly, but far better than any centralized system.
The only effective and scalable solution to social media moderation/curation/mediation is to build distributed middleware services, plus tools for orchestrating the use of a selection of them to compose our individual feeds. That too can be done well or badly, but only with a collective effort to do our best on a suitably distributed basis can we succeed.