On how governance institutional designs cannot restrain corporate, criminal and political groups of humans who gain increasing power from training and exploiting increasingly more capable – eventually power-seeking – machine learning architectures.

As elaborating on the human-to-human stage of the previous post.


Excerpts compiled below:

  > How can governments and companies 
  > cooperate to reduce misuse risks from AI
  > and equitably distribute its benefits?

• that people and governments
  simply do not have any way
  to understand and mitigate
  the significant advantage
  that companies having and deploying AI
  have, in regards to their own capabilities.
• that the governance challenges perceived 
  by many/most regular American people
  to be the most likely to be impactful
  to individual people "soon"
  (ie, within the next decade)
  and which where also considered
  by them to be "the highest priority,
  most significant/important issues", etc,
  in regards to AI, machine learning,
  and enhanced use of technology general,
  were:

     > 1. "Preventing AI-assisted surveillance
            from violating privacy and civil liberties".

     > 2. "Preventing AI from being used
             to spread fake and harmful content online".

     > 3. "Preventing AI cyber attacks
             against governments, companies,
             organizations, and individuals".

     > 4. "Protecting data privacy".

• that the issues listed by the common people,
  as being of 'primary concern',  
  are actually less likely to be personally noticeable
  than the use of AI tools by criminals
  by businesses engaged in predatory practices,
  by cultural/cult leaders (operating in their own interests),
  politicians with predominately privatize interests, etc,
  to do the kind of sense making (perception)
  and action taking (expression)  
  as necessary to create better honeypots,
  more, deeper, and more complex entanglements,
  and to implement more effective and efficient
  extraction and extortion of resources
  at higher frequency, intensity, consequentiality,
  at larger scale, more quickly,
  invisibly/transparently/covertly, etc,
  in more and more ways
  that are more and more difficult
  to avoid, prevent, mitigate, and heal/restore from,
  for larger and larger and more varied
  fractions of the population, etc.
• where/moreover, as these tools
  become and more widespread, effective, etc;
  that more and more people will be using them,
  and/or find that they have to use them,
  in order to remain competitive to their neighbors
  (ie; as per any other/similar multi-polar trap scenario)
  such that the prevalence and variety
  of such traps, risks, harms, costs, etc,
  everywhere increases, systemically,
  with universal extraction occurring 
  to such an extent, in so many ways,
  for so many resource kinds,
  with so many degrees of resource motion
  that is overall globally unconscious,
  that the net effect is eventual inexorable 
  system/civilization/cultural collapse.
• that the overall effect
  of introducing AI/machine learning,
  is that it ends up being used
  for more effective social pathology,
  as evidenced in increasing occurrence
  of sophisticated bank fraud, stock market 
  manipulation, back room dealing 
  and government bailouts, etc.
  •  that most people do not actually realize/understand
     the actual most likely risks/hazards/costs
     associated with widespread AI use/deployment.
     - as including people in government.
     

  > Can existing governments
  > be used to prevent or regulate the use
  > of AI and/or other machine learning tech
  > by predatory people in predatory ways?

• as in: 
  Can goverments make certain harmful, risky,
  or socially costly activities illegal, and yet also 
  to be able to effectively enforce those new laws?
• as to actually/effectively protect individuals/groups
  from the predatory actions, of other AI/machine/weapon 
  empowered individuals/groups, in ways that favor:
  1. making the right outcome much more likely
     (as individually and socially beneficial)
      than the wrong/harmful outcome.
  2. early detection of risk, harms, costs,
     law violations, etc.
  3. the effective, complete proactive mitigation
     of such risks/harms/costs, etc.
  4. the restoration and healing of harm,
     reparation of cost, etc, as needed 
     to restore actual holistic wholeness,
     of individuals, families, communities, 
     cultures, etc.
      
• ^– where in general, no; not with 
  governance structures/methodologies
  currently in place.
  • that only much more effective,
    actual good governance structures
    will have any hope of actually mitigating
    the real risks/costs/harms
    of any substantial new technology
    based on complexity itself
    (ie, examples as AI, machine learning,
      biotech, pharmaceuticals,
      and all intersections and variants of these).
• where in a/any contest between people savvy with AI use,
  and the rate of change of that technology, and its use,
  and the likely naivety of people in government
  attempting to regulate that AI, its use, etc,
  and the fact of extensive, very well funded,
    industry lobbyists
    all being (much) more knowledgeable, skillful,
    and moreover themselves empowered
    with the use of the tech itself,
    so as to either influence the policy makers,
    or to be/become the policy makers themselves,
    and thus to be serving their own interests
    (rather than the interests of the actual public good);
    that the chances that anyone
    who actually has the public interest in mind,
    and somehow manages, by complete accident,
    to find themselves at a government post,
    that they will for sure have too many things --
    of way too much complexity, concurrently occurring --
    for such ostensive government regulators
    to have or provide whatever sufficient amount of
    attention and understanding,
    that would actually be needed,
    to regulate that AI and machine learning industry,
    and/or its applications and/or uses,
    in anything at all approaching any sort of
    effective and actually risk mitigating manner,
    even when considered for acute problems only,
    leaving alone the complete unaddress of long term problems.
      - as consistent with nearly all historical precedent.
• that artificial inteligence 
  are tools in the hands of psychopaths,
  who also in their completeness of
  being incapable of feeling the pain of others,
  or in being characteristically and unusually unable
  to relate to such feelings,
  or feelings/meaning/value in/of,
  or in association with, other humans at all,
  as conscious, alive, and worthwhile beings,
  with value, meaning, and agency,
  a will and sovereignty of their own.
  • where psychopaths have aligned tenancies
    with the nature of the machines themselves,
    that this near perfect mating
    of solely personal benefit agency
    with the soulless yet adaptable responsive 
    nature of the machine intelligence process,
    makes for a significantly enhanced psychopath
    with new superpowers.
• where leaders
  (either in business or governance,
    though more typically in business)
  have learned to 'do whatever it takes'
  to climb the social ladder
  (on the backs of whomever)
  to 'win regardless of whatever cost'
  (to others, and maybe to (future) self),
  that such machine learning tools
  become indispensable to the operations
  of the business itself, enabling 
  increased efficiency of extraction
  across all networks of capability.
  • as combining Metcalfe's law 
    with network commerce
    to build the ultimate parasitic system,
    intimately hostile to all humans,
    and possibly to all of life,
    through the will and agency
    of the humans who elect to use such tools,
    and/or moreover may be required to use such tools,
    so as to effectively continue to compete with
    (their illusion of) (the capabilities of) "the other guy".
     
• that new governance (and economic) architectures
  will be needed, which are inherently anti-psychopathic, 
  anti- corruptible, to be anywhere near in capability 
  to dealing with situations like this.

→ Read link to Forrest Landry's blog for more. 

Note: Text is laid out in his precise research note-taking format.