Blockchain Thinking: The Brain as a DAC (Decentralized Autonomous Corporation)

Blockchains are a new form of information technology that could have several important future applications. They could be an explosive operational venue for new kinds of autonomous agents like DACs, distributed autonomous corporations. A DAC is a corporation run without any human involvement through a set of business rules based in software code. It is called a ‘corporation’ because it typically engages in corporate operations like fundraising, providing services, and making profits for shareholders. Blockchains are a software protocol upon which digital cryptocurrencies like Bitcoin run.

One potential application is blockchain thinking, formulating thinking as a blockchain process. This could have benefits for both artificial intelligence and human enhancement, and their potential integration. Blockchain thinking could be conceived as an input-processing-output computational system with several features whose benefits might include the ability to orchestrate digital mindfile uploads, advocate for digital intelligences in future timeframes, implement smart-contract based utility functions, instantiate thinking as a power law, and facilitate the enactment of Friendly AI.

Top 4 Killer Apps: Brain as a DAC:

1. Friendly AI – Digital intelligences will likely not be running in isolation, they will want to conduct operations on smartnetworks that are possibly managed by consensus models or other mechanisms. Any agent wanting to conduct transactions on a smartnetwork will need to be in good reputational standing to do so. Smartnetwork operations could include accessing information and other resources, fund-raising, entering into contracts, and offering services. The consensus only validates and records bonafide transactions from ‘good’ agents. Thus only friendly players would be able to have their transactions executed, and that is how friendly AI could be enacted. There are some objections to this argument, but the key point is that blockchains are a checks-and-balances system that could potentially encourage certain kinds of behavior.
2. Blockchain Deep-Learners: A crucial moment in AI research was finally having large enough data stores over which to run machine learning algorithms. Google demonstrated this with news, translation, and most recently image recognition of cats in YouTube videos. A similar ‘big data’ argument can be made for thinking where large databases of personal connectome files might lead to an understanding of how thoughts are actually represented in the brain. This understanding could inspire new classes of AI applications. As is currently being explored for EMRs and personal genomes, blockchains could be a useful privacy and access control mechanism for permissioning different parties to the large and sensitive data files more granularly Personal connectome files could also be orchestrated by blockchain processes.
3. Blockchain Advocates - One of the great potential benefits of blockchains could be instantiating smart contracts as your independent third-party advocates in uncertain future timeframes. An element of the business model that needs to be established is trustworthy oracles for confirming information. The Wikipedia of the future could be a blockchain-based oracle service to look up the current standard for digital mindfile processing, storage, and security as these standards would likely be advancing over time. “You are running on the current standard, Windows 36 and a Lloyd Quantanium 3,” your smart contract valet informs you. Thus, blockchain smart contract advocates could help digital intelligences and AI DACs feel more secure in their future survivability and also humans more comfortable in uploading their digital mindfiles.
4. Digital Mindfile Services – Already there may be many different representations of you online, and your digital identity. Over time these could become more explicitly a full and fidelitous ‘digital you’ for backup purposes (like stroke rehabilitation) or otherwise. There are already some existing online mindfile services like LifeNaut and CyBeRev. Presumably machine-learning and deep-learning algorithms will eventually crawl the web to assemble ‘digital you’ files in an automated manner, aggregating social media, photos, linkedin profiles, forum comments, academic or other published writings, etc. into a composite you, including with imputations about your value system and goals. Later brain scans and personal connectomes can be added to this data store, as well as real-time lifelogs, memory logs, idea logs, and EEG brain activity logs from quantified self EEG rigs. This could lead to being able to instantiate your mindfile as a DAC and personal thinking blockchains, enabled to carry out digital tasks on your behalf.

Beyond these killer apps of Blockchain Thinking, there could be more sophisticated uses of blockchains for computational thinking. One could be logging all of an agent’s memories and ideas as discrete units that are encoded, stored, and universally-accessible, perhaps with multiple copies and versions (such as the soft-hashing of ideas in development) that are then deployed in smart contract DACs. Another is that processing might be instantiated in a massively distributed architecture that is not available in human brains, yet still comprises the non-linearity of human thought. Third, blockchain thinking might give rise to new forms of consensus models such as self-mining ecologies and proof of intelligence, and make use of demurrage principles to redistribute brain currencies like ideas and long-term potentiation. Blockchains and blockchain thinking might be not just a tool for the immediate progress of intelligence, but also for the longer-term transition to a world of multispecies intelligence living cohesively and productively in digital societies.

More details: Texas Bitcoin Conference Presentation, Paper, Video

Cogntive Enhancement can Integrate Man and Machine

Cognitive enhancement should be conceived as the philosophical issue of the greater subjectivation possibilities for man, as opposed to primarily a bioethical concern. The current world is one in which man and technology are increasingly interlinked. One high-stakes endeavor is cognitive enhancement, of which there are different working definitions. A precise account is that cognitive enhancement is the augmentation of human skills, attributes, and competencies through the use of technology, medicine, and therapy designed to increase human performance capability (Hildt). Another is that it is the amplification or extension of core capacities of the mind through improvement or augmentation of internal or external information processing systems (Bostrom). Another is it refers to any expanded or new capacity of a human being (Buchanan). The salient distillation is that cognitive enhancement is the targeted improvement of natural human cognitive abilities.

The motivation for cognitive enhancement could be twofold. First, there are the obvious practical benefits of improved perception and memory. However, beyond this, more profoundly the reason for seeking improved cognition is the implication that it can facilitate our own growth and development as humans, actualizing ourselves and our potential more rapidly and effectively. Cognitive enhancement is an important topic for investigation because it examines our existence and also the human-technology relation. Increasingly powerful science and technology tools are emerging that may have the potential to dramatically enhance human performance, and perhaps redefine what it is to be human. Technology advances at a much higher rate than man subjectivates, and man and technology are increasingly being integrated together, with technology no longer being seen as an external tool, but as an embedded presence, such that man and technology are co-evolving and subjectivating together. The rights kinds of cognitive enhancement applications might be of benefit for both humans and technology entities, and their potential integration.

References
Bostrom, N., and Sandberg, A. (2009). "Cognitive enhancement: methods, ethics, regulatory challenges." Sci. Eng. Ethics 15, 311–341.
Buchanan, A. (2013). Beyond Humanity: The Ethics of Biomedical Enhancement. Oxford UK: Oxford University Press.
Hildt, E. and Franke, A.G., Eds. (2013). Cognitive Enhancement: An Interdisciplinary Perspective. Dordrecht DE: Springer.

Escaping the Totalization of my own Thinking

One of the highest-order things that we can do for ourselves and others is try to escape our own thinking style. Each of us has a way of thinking, a default of which we may not even be aware. Even if we are aware that we each have a personal thinking style, we may not think to identify it and contrast it with other thinking styles, consider changing our own style, and even what it might mean to be portable between thinking styles.

This is a form of the totalization problem, that being completely within something, it is hard to see outside of the totality of that thing. If we are thinking through our own mind, how can we possibly think or see anything that is not within this realm? By definition, this seems an impossible conundrum; how are we to see what is beyond what we can see? How can we become aware of what we are not aware?

The totalization problem has been an area of considerable philosophical focus, whether there is an exteriority (an outside) to concepts like world and reality, and if so, whether it is reachable. Philosophers like Jacques Derrida thought that yes, escaping totalization (any system that totalizes) would indeed be possible. One way is though literature, which offers its own universe (totalization) but also inevitably a hook to the outside (our world). Another way is through the concept of yes, assent, which has a hearing-party affirming and a talking-party asserting in a dynamic process that cannot be totalized.

In a less complicated way for our own lives, there can be other ways of escaping from the totalization of our thought into an exteriority, an outside where we can see things differently. Explicitly, we can try different ways of experiencing the world by learning other of how people apprehend reality, and noticing that more joy may come from experiencing the journey rather than attaining any endpoint. Perhaps most important is being attuned to new ideas and new ways of thinking and being, especially those that don’t automatically make sense.

What are Concepts and why are they Important?

As the French philosopher Deleuze articulates, the output of the scientist is quantitative characterization, the output of the artist is subjective experience, and the output of the philosopher is concepts. Far from being a dusty old topic of the past, philosophy is as vibrant as ever as there are many possibilities in concept innovation that can facilitate a heightened understanding of the world.

What is a Concept?
We can start by asking what is a concept? The dictionary definition of a concept is an abstract idea, a general notion. However bringing specific concepts to mind might not be something we are familiar with doing on a day-to-day basis. Starting to brainstorm some concepts, there seem to be different kinds...

Concepts: Applying to the Self
Some concepts seem practically applicable to the domain of personal experience, how individuals might understand themselves in relation to the world, concepts like karma, flexibility, acceptance, empowerment, self-actualization, extensibility, justice, self-identity, payback, barriers, rules, deferred gratification, and creating community.

Concepts: Phenomena greater than the Self
Another class of concepts seems applicable to phenomena greater than the self, ideas that model what is going on in the world like sustainability, globalization, digital divide, the bottom of the pyramid, the last mile, plasticity, the occupy movement, wearable electronics, the wireless Internet of things, augmented reality, healthspan, quality of life, and crowdfunding.

Concepts: Philosophical Concepts beyond Self and World to Configure a Range of Thinking
For Deleuze, there is another class of concepts, of philosophical concepts that are more extensive than personal and global concepts - a philosophical concept is not an identity condition or proposition, but a metaphysical construction that defines a range of thinking. Some examples of philosophical concepts are Plato's ideal forms of things, Kant's doctrine of our cognitive faculties, and Descartes’s cogito - the philosophic principle that one's existence is demonstrated by the fact that one thinks. As a branch of philosophy, in technology philosophy too, concepts too are defined in this Deleuzian metaphysical construction that defines and invites a range of thinking, some examples are articulated in A Conceptology of Technology Philosophy - Top 20 Technology Philosophy Concepts.

DIY Philosophy: Crowd Models to Democratize Participatory Thinking

The model for computing and info tech exploded with the PC and the Internet – democratizing the field across all strata and making it accessible to any interested individual. The worldwide technology and startup industry has boomed and proliferated as a result. DIY science is doing the same for crowdsourced labor, quantified self-tracking, biology hacking, and the shift to the 21st century health paradigm of preventive medicine. The field of philosophy is ripe for similar democratization – some tip-offs are that it is one of the few remaining areas comprised primarily of white males, and where memorization is still important.

Philosophy Improves Sophistication of Modern Thinking 
Philosophy is the sport of thinking – one of its great benefits is its broad applicability beyond the dusty academic discipline to one’s own personal thinking and lifestyle. A key contemporary use of philosophy is in helping to provide a deeper and more sophisticated means of understanding our fast-paced technologized modern world and our place therein. Many people are interested in philosophy but few have the affordance or interest for full-time involvement which has seemed to have been required given the notorious density and inaccessibility of philosophical works.

Crowd Models Facilitating Philosophy Accessibility 
Crowd models (analogous to the PC revolution) are starting to change the former inaccessibility of philosophy. Philosophy courses and reading groups are popping up at free public universities (the Public School, the University of the Commons), podcasts are acquiring significant listenership, and online communities and publications have growing participatory audiences (e.g.; e-Flux, Plasticities Sciences Arts).

FQXi for Philosophy
While there are some research institutes supporting philosophy like the University of London's Institute of Philosophy, one next step in creating the more overt sensibility of the DIY philosopher as the analog to the DIY scientist and software hacker would be to have Philosophy Research Institutes that specifically promote DIY philosopher participation through essay contests, conferences, and other acknowledgement and community-building activities – an FQXi (e.g.; a research institute encouraging speculative innovation in physics and cosmology) for philosophy is needed.

Big data facilitates new era of knowledge, education, and thinking

Big data and the internet continue their sweep across modern life by facilitating a new era of education, and possibly, thinking. As traditional educational institutions have become financial institutions intent on merchandizing their brands, students are finding other means of accessing educational content.

At present
Some of the newer models include MIT OpenCourseWare, the Khan Academy, Coursera, and Codecademy. These free or low-cost education services confer the direct benefit of their programs, and advantages by using the large numbers and real-time aspects of the internet to obtain and incorporate immediate feedback from growing student populations. This is leading to a better education product, and a mechanism for learning about learning.

The near future
A next stage could add course-level (rather than degree-level) accreditation and a basic algorithms interpretation layer à la Google Translate, Spell Check, and Ngram Viewer. Simple machine learning algorithms applied to large data sets could allow an expansion from quantitative testing to semantic testing (and more importantly, semantic living, in the sense of a broader intellectual life). Core knowledge elements could be identified in data corpora and reviewed for comprehension in student-produced material.

The farther future
Taken to its logical extreme, what if distance learning were to completely replace local educational institutions? Are there risks of homogenization of thought if everyone is taking the same classes from leading worldwide professors? Does personalized learning, via sommelier-assembled curricula, increase inherent biases that might otherwise be countered by institutional education? Does the U.S. need 5-10 philosophy/etc. professors at 5-10 universities per state? Clearly there are systemic aspects, and costs and benefits, of a more radical reinvention of education. These can be managed effectively through the lens of overall goals, perhaps the most important of which is extending the depth and capacity for thinking, both within individuals, and to more individuals.

Obtaining models for singularity futures thinking

The challenge is called out by science fiction writer Vernor Vinge as being related to the technological singularity, namely that any one future technology change could be so fundamental across all aspects of life that it is hard to write plausible science fiction, and more generally impacts how we think about the modern and future world. Any next node that has sufficient transformative power (e.g.; like the internet) could change things so fundamentally, globally, multi-dimensionally, and quickly that its impact would be essentially beyond cognition. Moreover, while there are some potential candidates visible for the ‘next internet’ such as smartphones, 3D printing, biotechnology, nanotechnology, and robotics, the real next node is likely to be an unforeseen discontinuity.

Comprehensive survey of thinking models
There is a paucity of models for thinking comprehensively and critically about the future in rigorous, sophisticated, justifiable, and transferable ways. A project that should be undertaken if not done so already is an examination of different models for structuring thinking from different disciplines. There is value in this at two levels: first generally in identifying, characterizing, and synthesizing different models for structuring thinking, and second in applying these models cross-disciplinarily to existing areas, and to new areas such as thinking about the future.

Eliciting explicit models for structuring thinking
The models that are used to structure thinking in different fields need to be made explicit. Practitioners immersed in fields may not be easily disposed to articulate these models. For example, it may be novel to inquire ‘What is the model for inquiry in this field?’ or even to have the concepts and vocabulary for explicating them.

Fields with models for structuring thinking
Some of the obvious fields to investigate for eliciting established models for structuring thinking are philosophy, complexity (complex adaptive systems, chaos theory, symmetry, etc.), computing (artificial intelligence, machine learning, knowledge representation, data management, etc.), systems-level disciplines (ecology, biology, cosmology, etc.), and social sciences (sociology, anthropology, economics, etc.).

The challenge of fishing structure and content from academic fields
Some of the immediate obvious barriers in accessing models for structuring thinking from academic disciplines are nomenclature and insularity. Semantic and conceptual nomenclature may prevent easy access to fields, but are largely a veneer that may be penetrated with a variety of translation techniques and concept mapping. Much more problematic is the potential lack of available suitable content in these fields. By default, many areas of academia are not externally-focused applied disciplines but rather inwardly-focused insular disciplines engaged in cataloging and interpreting the thoughts of their own ancestral brethren. The accompanying applied dimension to every field that would explicitly render the core ideas accessible, and proven and useful through deployment seems to be absent from many fields. Rather than being perceived as less pure of an exploit, the application of the central ideas and structures would seem to be a key raison d'être for these fields of knowledge.