Painting - Niki de Saint Phalle - Martyr Necessaire
In Swedish, " mot " means against. It also means " towards ".
Very incidentally, a background song I once heard embezzled a share of my attention. Not so much an interest in the genre nor the artist, but rather two words - " Ting ting ". The track was in spanish, but at a speed and intonation narrowly allowing me to apprehend more context. Unfailingly however - not in any language but experience I perfectly understood "Ting ting".
900+ million individuals now have a cross-border (international) connection on social media (Digital Globalization, Mckinsey & Company February 2016).
What experiential subsumption principles will establish degrees of intersubstitutivity between - information discovery and attention optimization?
Could a lower uncertainty of information, also known as information entropy exist where onomatopoeia can mend translation losses? What are meaningful cycles carrying IoT's interplay with centers and layers of urban planning and built environments that will engender those referents? What are ways P2P collaboration could benefit from newer activation concepts?
A caesura of curiosity mutters - in crowdsourced realms, what can be deduced from:
- intangible information (service) substantively based on relative certainty (trust as asset)?
- the collateralizing of demand, kept on par with overhead?
At an individual level decoupling sunk cost from risk aversion, a parallel appears to have space: An Expectation mobile application.
More than an occasional event - isn't expectation a component of trust whether an activity is process, user or outcome centric?
Could having a continuously monitored, conditionally shared, and validated sense of expectation nurture healthier collaborative information discovery, transactional, and larger p2p activities? Wouldn't there exist a score of ways to characterize one's expectations in almost any verifiable situation, and measure it against micro outcomes? Wouldn't this model peek into trading trust tokens? With enough points (at a given moment in time that is), some users could be eligible to become witnesses of scenarios requiring cross-discipline aptness.
A sample of impacts:
- Agent K has entered situation F (agreement, transaction, team project, lunch etc). Agent K had enough points to purchase agent L's expectations of outcome S. Agent L's expectations are logged in specific areas of interest, measured against results and shared with immediate network, buyers and public optionally.
- Agent D learns from some of his/her analytical weaknesses by seeing how the logged expectations were demonstrated invalid.