Solutions: Mapping Consensus Optimization

Solutions: Mapping Consensus Optimization

Is the Internet as we know it today a result of a random sample of accidental successes? Or is it the net effect of bias to some universe of interests? If the former is the case, then the functions of Internet governance are the means to reduce friction inside the current state of affairs, and the law of averages shall continue a normal distribution of Internet successes throughout any given nation or nations. If the latter is the case, then the purpose of Internet governance is to normalize a distribution of benefit emerging from the globalized Internet, stimulating equitable competition and tempering amalgamated control.

The barrier to broad consensus on the equity of a distribution is proportional to the diversity of its constituents, and is further characterized by propinquity and consonance. In absence of formal constructs to marginalize the adverse effects of these characteristics, consensus will equate equity and equality through some arbitrary standard, and marginalize the balance in full favor of the most established neighborhood of like-minded associates.

In the spirit of a solution consider a system that maximizes multistakeholder consensus through reference to a moving average of scores elected by participants. Should such a system internally compute an average nominally weighted by participant magnitude, it would render inequity to many a nation relatively shy of measure. Should the system compute the average without accounting for constituent magnitude, it could be inequitable to those whom invested the most in infrastructure. Thus, the proper response of such a system must reflect influence while preserving equity, over a large ordinal number of participating opinions.

If the collective opinion range is drawn symmetrically about the reference, and each side is segmented to a standard fraction from its respective mean, then each segment shall hedge knowledge to seed a function that reflects equity and equality. The final result on either side of the reference interprets forward levels of assent or dissent, and defines natural signals for consensus. The general elements of influence that arbitrate amplitudes and latencies predominating harmonics are required by functions to harmonize key segments, and should effect to preserve equity between national actors as well as between people. Some unison must originate from the natural lattice of gain such that an influence curve is economically indicative of globally directed participants in addition to their congruent public counterparts. Furthermore, the weighted pairing of symmetric indicators that describe influence curves to either side of the reference should intrinsically estimate the product of equality between national counterparts.

The loaded average describing each independent national opinion produces a stack of inputs to be matriculated inside either neural network deciding levels of assent or dissent in reference to the initial absolute mean. The processed average yield represents an iteration of relevant consensus on that which is subject to deliberation. A feedback mechanism should exist to provide a nominal exponentially decaying reward or penalty in a series of ingemination, such as relative to the ends of the spectrum of positive opinion velocities with respect to the reference.

The conclusion of an iterance effectuates publication of consensus and individual opinion scores. A multilateral body indirectly stimulates convergence of the system by advising parameters to instantiate deliberation, such as the per-iterance discussion time, acceptable consensus levels, and multistakholder consensus system feedback variables. Other parameters such as loading for each national average may be globally initialized to some reasonable (eg. Government: 16%, Academia: 12%, Civil: 28%, NGO: 8%, Private: 24%, Tech: 12%) default and later refined by category using the system. Consensus maximum is generated by sequential iterance wherefrom discussions are reopened until new votes are to be considered to support upstream input. Thus, only the thrust of global action, through a resounding participation on equal footing, may dictate the outcome that achieves equity.

The primary challenge to success is in achieving buy-in from a diverse set of actors on the global stage. In this regard, the development of the system should be the result of an international team effort, as selected by each contributing member to create an agile and equitable private organization that meets a predefined set of criteria. Similarly, on the technical front, the system architecture should allow for a mirror of live executable code as well as a delayed and obfuscated view of the database. In its foreseeable future of self-sufficiency it should enable applications such as issue identification, entity and policy alignment, opinion demographics, dispute resolution, and even adjudication considering that compliance may be enforced through penalty to contribution weight. As a result, global stakeholders will have a need to collaborate on issues during iterative consensus taking, and an alignment mechanism to create, organize, and support their working groups is suggested.

A systemic processing of contributory assent remains equitable to all stakeholders notwithstanding state variability in any density or distribution of participation. It preserves a balance between economic influence and nation equality to empower a number of future applications. While complex in terms of description, an electronic system facilitating the globalization of Internet governance is no more complicated than any of a myriad of services that exist today. Nevertheless, only a multistakeholder consensus system tangential to the efficient frontier of Internet successes, and created through the integrity and courage of leadership, may secure an equitable future for our digital existence.

General references:

H. Yang, H. Wang, H. Karimi: Robust Adaptive Neural Backstepping Control. (2014)

I. Krajbich, D. Lu, C. Camerer, A. Rangel: The attentional drift-diffusion model. (2012)

I. Douven, A. Riegler: Extending the Hegselmann-Krause Model. (2011)

F. Dietrich: Scoring rules for judgment aggregation. (2011)

P. Domenech, JC. Dreher: Decision Threshold Modulation in the Human Brain. (2010)

A. Pluchino, V. Latora, A. Rapisarda: Compromise and Synchronization in Opinion Dynamics. (2006)

R. Bogacz, E. Brown, J. Moehlis, P. Holmes, J. Cohen: The Physics of Optimal Decision Making. (2006)