Kurzweil, R. (2020 May 19). AI-Powered Biotech Can Help Deploy a Vaccine In Record Time. Wired. https://www.wired.com/story/opinion-ai-powered-biotech-can-help-deploy-a-vaccine-in-record-time/

Yang Yang: The Replicability of Scientific Findings Using Human and Machine Intelligence (Video). Metascience 2019 Symposium. https://www.metascience2019.org/presentations/yang-yang/

Yang, Y., Youyou, W., & Uzzi, B. (2020). Estimating the deep replicability of scientific findings using human and artificial intelligence. Proceedings of the National Academy of Sciences, 117(20), 10762–10768. https://doi.org/10.1073/pnas.1909046117

Halim, S. (2019, August 13). How Artificial Intelligence can revolutionise healthcare. Health Europa. https://www.healtheuropa.eu/how-artificial-intelligence-can-revolutionise-healthcare/92824/

Lanovaz, M., & Turgeon, S. (2020). Tutorial: Applying Machine Learning in Behavioral Research [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/9w6a3

Mei, X., Lee, H.-C., Diao, K., Huang, M., Lin, B., Liu, C., Xie, Z., Ma, Y., Robson, P. M., Chung, M., Bernheim, A., Mani, V., Calcagno, C., Li, K., Li, S., Shan, H., Lv, J., Zhao, T., Xia, J., … Yang, Y. (2020). Artificial intelligence for rapid identification of the coronavirus disease 2019 (COVID-19). MedRxiv, 2020.04.12.20062661. https://doi.org/10.1101/2020.04.12.20062661

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World Pandemic Research Network

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Informa Group, que posee editoriales como Taylor & Francis, de Informa Intelligent Division toma medidas en su sector de conferencias y eventos. Provee dos tercios de sus ingresos totales, 2.9 billion dólares. Emite acciones y para el mercado norteamericano acuerdos de deuda. Mientras la parte editorial que aporta un 35% de los ingresos se mantiene sin cambios y con pronósticos estables y sólidos. Stephen Carter CEO

fonction de l’espace public: un appareil critique (la critique est productrice d’espace public).

le pouvoir, pour maintenir sa légitimité, doit être exposé à la sphère publique et se montrer à lui avec transparence; il doit pouvoir être challengé; s’il ne résiste pas à la critique publique, il ne mérite pas d’être en place.

la possibilité de challenger l’instance publique est comparable à la publication des protocoles de sécurité utilisées dans le domaine public (ex. SSL/TLS): la sécurité des contenus encryptés tirent justement leur robustesse du fait que leur algorithme est public; quiconque pourrait le challenger à tout moment, si bien qu’on s’assure d’en éliminer toutes les failles (et l’intelligence collective peut être mise à contribution, le cas échéant).

Argument en faveur de l'IA qui permet bien de gérer le flux mais ajoute un second bénéfice : proposer un parcours idéal. Ce bénéfice supplémentaire peut être considéré comme un argument réthorique de type Logos.

Argument épistémique inductif et réthorique de type logos.

On passe à l'intelligence artificielle, technologie de pointe. Apporte du crédit à l'affirmation du bénéfice du numérique.

throw out this factoid when doing video?

Sense Collective's TotemSDK brings together tools, protocols, platform integrations and best practices for extending collective intelligence beyond our current capabilities. A number of cryptographic primitives have emerged which support the amazing work of projects like the NextNow Collaboratory in exciting ways that help to upgrade the general purpose social computing substrate which make tools like hypothes.is so valuable.

Seymour Papert, had an approach that provides a nice synthesis between these two camps, buy leveraging early childhood development to provide insights on the creation of AI.

Intelligence amplification over artificial intelligence. In reality you can't get to AI until you've mastered IA.

Tags were used for discovery of specific types of content. Who needs that now that our new overlords of artificial intelligence and algorithmic feeds can tell us what we want to see?!

Of course we still need tags!!! How are you going to know serendipitously that you need more poetry in your life until you run into the tag on a service like IndieWeb.xyz? An algorithmic feed is unlikely to notice--or at least in my decade of living with them I've yet to run into poetry in one.

Some great blue sky ideas here.

A multimedia approach to affective learning and training can result in more life-like trainings which replicate scenarios and thus provide more targeted feedback, interventions, and experience to improve decision making and outcomes. Rating: 7/10

A blended learning approach to emotional intelligence is the methodology for the course created by Google and implemented in various institutions around the globe. Rating: 8/10

An emotional intelligence course initiated by Google became a tool to improve mindfulness, productivity, and emotional IQ. The course has since expanded into other businesses which report that employees are coping better with stressors and challenges. Rating: 7/10 Key questions...what is the format of the course, tools etc?

what is intelligence after all?

is having will or intention akin to having intelligence?

Is it just that how we all learn and evolve? 😲

HTM and SDR's - part of how the brain implements intelligence.

"In this first introductory episode of HTM School, Matt Taylor, Numenta's Open Source Flag-Bearer, walks you through the high-level theory of Hierarchical Temporal Memory in less than 15 minutes."

But we have to be careful not to inadvertently favour the big tech companies in trying to stop favouring the big EMR providers.

AI is controlled by these external forces. In what direction will this lead it?

Mere consent isn't enough. We consent to give away all sorts of data for phone apps that we don't even really consider. We need much stronger awareness, or better defaults so that people aren't sharing things without proper consideration.

This is part of the habit and culture of data use. And it's very different in health than in other sectors, given the sensitivity of the data, among other things.

Advancing AI requires more than just AI stuff. It requires infrastructure and changes in human habit and culture.

Another issue with complex systems: the data can be volumous but poor individual quality, relying on domain knowledge to be able to properly interpret (eg. that doctor didn't really prescribe 10x the recommended dose. It was probably an error.).

AI depends on:

• static processes - if the population you are predicting changes relative to the one used to train the model, all bets are off. It remains to be seen how similar they need to be given the brittleness of AI algorithms.
• homogeneous population - beyond race, what else is important? If we don't have a good theory of health, we don't know.

What about examples of future sorts of annotations/redactions like these with emerging technologies? Stories about deepfakes (like Obama calling Trump a "dipshit" or the Youtube Channel Bad Lip Reading redubbing the words of Senator Ted Cruz) are becoming more prevalent and these are versions of this sort of redaction taken to greater lengths. At present, these examples are obviously fake and facetious, but in short order they will be indistinguishable and more commonplace.

This reminds me of this Reddit page

The page takes pictures and texts from other Reddit pages and uses it to create computer generated posts and comments. It is interesting to see the intelligence and quality of understanding grow as it gathers more and more information.

Volume of Activity

Technical Performance

Technical Performance

Technical Performance

Volume of Activity

Volume of Activity

Volume of Activity

Etienne's blog! Amazing resource for OSINT; particularly focused on technical attacks.

Saying it's a "bug" implies that it's bad. But something this significant likely improves our evolutionary fitness in the past. This "bug" is more of a previously-useful adaptation. Whether it's still useful or not is another question, but it might be.

Collective Intelligence Playground

Ashley Norris is the Chief Academic Officer at ProctorU, an organization that provides online exam proctoring for schools. This article has an interesting overview of the negative side of technology advancements and what that has meant for student's ability to cheat. While the article does culminate as an ad, of sorts, for ProctorU, it is an interesting read and sparks thoughts on ProctorU's use of both human monitors for testing but also their integration of Artificial Intelligence into the process.

Rating: 9/10.

Again, this doesn't conflict with a machine-learning or deep-learning or neural-net way of seeing IP.

Or, the copy initially made is changed over time since human "memory" is interdependent and interactive with other brain changes, whereas each bit in computer memory is independent of all other bits.

However, machine learning probably results in interactions between bits as the learning algorithm is exposed to more training data. The values in a deep neural network interact in ways that are not so obvious. So this machine-human analogy might be getting new life with machine learning.

I don't see how this is true. The IP perspective depends on algorithms. There are many different algorithms to perform various tasks. Some perform reverse-kinematic calculations, but others conduct simpler, repeated steps. In computer science, this might be dynamic programming, recursive algorithms, or optimization. It seems that the IP metaphor still fits: it's just that those using the metaphor may not have updated their model of IP to be more modern.

There is no wonder that AI gains popularity. A lot of facts and pros are the stimulators of such profitable growth of AI. The essential peculiarities are fully presented in the given article.

This suggests that Joe is doing something almost completely unrecognizable--with language at least. I guess my assumption is that I would know what Joe was doing he'd just be doing it so quickly I wouldn't be able to follow. And he'd complete the task--a task I recognize--far more quickly than I possibly could using comparable analog technologies. Perhaps this is me saying, I buy Englebart's augmentation idea on the level of efficiency but remain skeptical or at least have yet to realize it's transformative effect on intellect itself.

I'm thinking about the role of AI tutors/advisors here. How often do they operate in the kind of flexible way described here. I wonder if they can without actual human intervention.

Engelbart explicitly noted that what he was trying to do was not just hack culture, which is what significant innovations accomplish, but to hack the process by which biological and cultural co-evolution has bootstrapped itself to this point. Culture used the capabilities provided by biological evolution -- language, thumbs, etc. -- to improve human ways of living much faster than biological evolution can do, by not just inventing, but passing along to each other and future generations the knowledge of what was invented and how to invent. Engelbart proposes an audio-visual-tactile interface to computing as a tool for consciously accelerating the scope and power of individual and collective intelligence.

To me, this is the most prescient of Engelbart's future visions, and the seed for future study of culture-technology co-evolution. I talked with Engelbart about this passage over the years and we agreed that although the power of the artifacts, from RAM to CPU speed to network bandwidth, had improved by the billionfold since 1962, the "softer" parts of the formula -- the language, methodology, and training -- have not advanced so much. Certainly language, training methods and pedagogy, and collaborative strategies have evolved with the growth and spread of digital media, but are still lagging. H/LAMT interests me even more today than it did thirty years ago because Engelbart unknowingly forecast the fundamental elements of what has come to be called cultural-biological co-evolution. I gave a TED talk in 2005, calling for an interdisciplinary study of human cooperation -- and obstacles to cooperation. It seems that in recent years an interdisciplinary understanding has begun to emerge. Joseph Henrich at Harvard, for one, in his recent book, The Secret of Our Success, noted:

Drawing insights from lost European Explorers, clever chimpanzees, hunter-gatherers, cultural neuroscience, ancient bones and the human genome, Henrich shows that it’s not our general intelligence, innate brain power, or specialized mental abilities that explain our success. Instead, it’s our collective brains, which arise from a combination of our ability to learn selectively from each and our sociality. Our collective brains, which often operate outside of any individual’s conscious awareness, gradually produce increasingly complex, nuanced and subtle technological, linguistic and social products over generations.

Tracking this back into the mist of our evolutionary past, and to the remote corners of the globe, Henrich shows how this non-genetic system of cultural inheritance has long driven human genetic evolution. By producing fire, cooking, water containers, tracking know-how, plant knowledge, words, hunting strategies and projectiles, culture-driven genetic evolution expanded our brains, shaped our anatomy and physiology, and influenced our psychology, making us into the world’s only living cultural species. Only by understanding cultural evolution, can we understand human genetic evolution.

Henrich, Boyd, and RIcherson wrote, about the social fundamentals that distinguish human culture's methods of evolving collective intelligence in The Origin and Evolution of Culture:

Surely, without punishment, language, technology, individual intelligence and inventiveness, ready establishment of reciprocal arrangements, prestige systems and solutions to games of coordination, our societies would take on a distinctly different cast. Thus, a major constraint on explanations of human sociality is its systemic structure

This explains my personal experience here: https://hyp.is/EIfMfivUEem7SFcAiWxUpA/epic.org/privacy/global_entry/default.html (Why someone who had Global Entry was flagged for a police incident before he applied for Global Entry).

Intelligence checks is very concerning here as it suggests pretty much what has already been leaked, that the US is running complex autonomous screening of all of this data all the time. This also opens up the possibility for discriminatory algorithms since most of these are probably rooted in machine learning techniques and the criminal justice system in the US today tends to be fairly biased towards certain groups of people to begin with.

This re-affirms the previous annotation that the set of training data for the intelligence checks the US runs on global entry data is biased towards certain groups of people.

Interestingly enough, we saw it coming. All the advances in technology that lead to this much efficiency in technology, were not to be taken lightly. A few decades ago (about 35 years, since the invention of the internet and online networks in 1983) people probably saw the internet as a gift from heavens - one with little or any downsides to it. But now, as it has advanced to such an extreme. with advanced machines engineering, we have learned otherwise. The hacking of sites and networks, viruses and malware, user data surveillance and monitoring, are only a few of the downsides to such heavenly creation. And now, we face the truth: machine intelligence is not to be underestimated! Or the impact on our lives could be negative in years to come. This is because it will only get more intense with the years, as technology further develops.

AI software and the chatbots will be included in the current technologies and have automated with the robotic system. They will have given rights to access calendars, email accounts, browsing history, playlists, past purchases, and media viewing history. 6% is the huge number in the world as people would be seen struggling in finding the jobs. But there are benefits also as your work would have done easily and speedily

Another important implication of the study.

This is absolutely essential to understanding the implications of the article.

Colom also suggested this (see link above). The fact that three people independently had this concern that age could be a moderator variable is telling. I'm glad the peer reviewers had us do this post hoc analysis.

This is particularly strong evidence for me. If g doesn't exist, these researchers would be the most likely ones to gather data to show that.

I suspect that this factor was so strong because it consisted of only four observed variables, and three of them were written measures of verbal content. All of the verbal cariables correlated r = .72 to .89. Even the "non-verbal" variable (numerical ability) correlates r = .72 to .81 with the other three variables (Rehna & Hanif, 2017, p. 25). Given these strong correlations, a very strong first factor is almost inevitable.

This factor may be weak because the sample consists of Sudanese gifted children, which may have restricted the range of correlations in the dataset.

My colleague, Roberto Colom, stated in his blog (link below) that he would have discarded samples with fewer than 100 individuals. This is a legitimate analysis decision. See his other commentary (in Spanish) at https://robertocolom.wordpress.com/2018/06/01/la-universalidad-del-factor-general-de-inteligencia-g/

It was this reasoning that led to the decision to conduct this study. There is mounting evidence that g exists in other mammalian species, and it definitely exists in Western cultures. It seemed really unlikely that it would not exist in non-Western groups. But I couldn't find any data about the issue. So, time to do a study!

Also, cats:

Warren, J. M. (1961). Individual differences in discrimination learning by cats. The Journal of Genetic Psychology, 98, 89-93. doi:10.1080/00221325.1961.10534356

After the manuscript was accepted for publication and the proofs turned in, I re-discovered the following from Gottfredson (2003, p. 362): ". . . lay beliefs are interesting but their value for scientific theories of intelligence is limited to hypothesis generation. Even if the claim were true, then, it would provide no evidence for the truth of any intelligence theory . . ."

Gottfredson, L. S. (2003). Dissecting practical intelligence theory: Its claims and evidence. Intelligence, 31, 343-397. doi:10.1016/S0160-2896(02)00085-5

To me, this is the way to create tests of intelligence for non-Western cultures: find skills and manifestations of intelligence that are culturally appropriate for a group of examinees and use those skills to tap g. Cross-cultural testing would require identifying skills that are valued or developed in both cultures.

John W. Berry is a cross-cultural psychologist whose work stretches back over 50 years. He takes the position (e.g., Berry, 1986) that definitions of intelligence are culturally-specific and are bound up with the skills cultures encourage and that the environment requires people to develop. Therefore, he does not see Western definitions as applying to most groups.

After this study, my position is more nuanced approach. I agree with Berry that the manifestations of intelligence can vary from culture to culture, but that underneath these surface features is g in all humans.

This one is a pretty bold statement to make, in general.

Mike Johansson, at Rochester Institute of Technology, makes the case that curiosity is the key to enabling both Creative and Critical Thinking for better problem solving, in general.

What are some of your ideas?

To me, this is the "take home" message of the article. I hope psychology educators do more to improve the accuracy of their lessons about intelligence. I also hope more programs add a course on the topic to their curriculum.

When I learned this, it blew my mind.

Ironically, there is research showing that video game performance is positively correlated with intelligence test scores (e.g., Angeles Quiroga et al., 2015; Foroughi, Serraino, Parasuraman, & Boehm-Davis, 2016).

Not every inaccurate statement in the textbooks was as silly as this one. Readers would benefit from browsing Supplemental File 2, which

This is a study begun in the 1970s of African American, interracial, and other minority group children who had been adopted by White families in Minnesota. The 1976 results indicated large IQ boosts (about 12 points) for adopted African American children at age 6, compared to the average IQ for African Americans in general. However, the 1992 report shows that the advantage had faded to about 6 points when the children were aged 17 years. Generally, intelligence experts see this landmark study as supporting both "nature" and "nurture."

Although the Stanford-Binet is historically important, the Wechsler family of intelligence tests have been more popular since the 1970s.

I wrote this sentence. Two coauthors, three peer reviewers, and an editor all read it multiple times. No one ever asked for it to be changed.

I have a Twitter moment that analyzes Gardner's book "Frames of Mind" and shows why this theory is poorly supported by empirical data. https://twitter.com/i/moments/1064036271847161857

We discussed this point with a reporter for an article that made the front page of the local newspaper: https://www.heraldextra.com/news/local/education/college/uvu/uvu-researchers-found-incorrect-info-in-percent-of-psychology-textbooks/article_6a84fddd-3dba-59bb-9a7e-ed957619ff20.html

Christian Jarrett of the The British Psychological Society found this as the main message of the article. Read his blog post at https://digest.bps.org.uk/2018/03/08/best-selling-introductory-psychology-books-give-a-misleading-view-of-intelligence/

A blog post by James Thompson (psychology professor emeritus at University College London) has a much more acerbic response to the study than this. See his blog post for a contrasting viewpoint: http://www.unz.com/jthompson/fear-and-loathing-in-psychology/

"Psychology Today" article on this study: https://www.psychologytoday.com/us/blog/brainstorm/201803/psychology-textbooks-contain-inaccuracies-intelligence

This article is a classic, and it is required reading in my undergraduate human intelligence course. If you only have time to read 1 article about intelligence, this should be it.

Definition of critical technical practice.

This approach is grounded in AI rather than HCI

(verbatim from the paper) "CTP consists of the following moves:

• identifying the core metaphors of the field

• noticing what, when working with those metaphors, remains marginalized

• inverting the dominant metaphors to bring that margin to the center

• embodying the alternative as a new technology

So then we know that most people will use supervised learning that requires less computational power and knowledge.

Synergy.

How emotional intelligence affects collaboration.

Emotional intelligence helps increase collaboration.

Key take-away from this research is that a positive outlook from the trainees on the training helps students learn new technology.

Es sieht für mich nicht eigentlich so aus als wären wir jemals die "Herren des Verfahrens" gewesen. Und auch darum geht es ja bei Marx. Denke ich.

The rhetoric of this passage raises a very important question. Are the people who are taking this drug really themselves still? If this was just a thought enhancing drug then perhaps this would be the case, however it does more than just make the user hyper-intelligent. The fact that this drug changes people's attitudes and their personalities proves that these people aren't themselves. On the other hand a hyper-intelligence may not directly change the person, but may enable them because a higher intelligence could reasonably lead to a higher confidence and a higher rationale of thinking.

If humanity were to create an ultra-intelligent computer then humans would be far surpassed. This part of the passage says that because our minds would be so simple compared to that of the machines at the point of the singularity that we would be little more than rabbits. This idea is astounding because our mental capabilities are vastly superior to those of rabbits or other animals and the idea that we could be so easily surpassed and so greatly surpassed is probably terrifying to many people. This is probably what makes the idea of a singularity such an abstract idea.

The authors of the text are proposing a radically different approach to the inevitable "singularity" event. They propose the research and development IA, or Intelligence Amplification, is developing computers with a symbiosis with humans. Noting that IA could be easier to develop than AI algorithms, since humanity had to probe what their true weaknesses and strengths are. In turn, developing an IA system that could cover humanities' weaknesses. This would summarily prevent an IA algorithm from getting over itself, which could potentially slow a point when we reach singularity.

This scene, as with many others, represents a crucial point in the movie. I think this also has some connection of what was discussed on the first day of class in relations to singularity. One student suggested that singularity in an astronomical context seems to be a black hole that implodes on itself. Further discussed in a linguistics context, we described how singularity shares connections with being alone or unique and individual. In the "into the wormhole" scene in 2001: A Space Odyssey, all of humankind is erased except for David. Advancements in technology had reached its peak to a point where David literally enters a black hole or a worm hole, in which he lives the rest of his life alone and passes away quietly. This signifying mankind imploding on themselves and being reborn. His passage signifies the rebirth of humankind and presents the idea of the cycle of life, where technology is nonexistent and life begins again. There is a sense of reverse chronology in the movie as the ending scene is continued at the beginning of the movie where the monkeys demonstrate their journey towards intelligence once more.

Diverse labor force is also a central principle of effective crowdsourcing and collective intelligence.

Collective intelligence definition.

Per the authors, "collective intelligence is a superset of social computing and crowdsourcing, because both are defined in terms of social behavior."

Collective intelligence is differentiated from human computation because the latter doesn't require a group.

It is differentiated from crowdsourcing because it doesn't require a public crowd and it can happen without an open call.

How data structure influences value systems and social practices is a much-needed topic of inquiry.

Big, sweeping statement that helps frame how big data could be better conceptualized as a complex, socially contextualized, temporal artifact.

I don't understand what Burns is arguing here. Who is he referring to claims that DHN is a "savior" or "the solution" to crisis response?

"Big data should therefore be be conceptualized as a framing of what can be known about a humanitarian crisis, and how one is able to grasp that knowledge; in short, it is an epistemology. This epistemology privileges knowledges and knowledge- based practices originating in remote geographies and de- emphasizes the connections between multiple knowledges.... Put another way, this configuration obscures the funding, resource, and skills constraints causing imperfect humanitarian response, instead positing volunteered labor as ‘the solution.’ This subjectivity formation carves a space in which digital humanitarians are necessary for effective humanitarian activities." (Burns 2015: 9–10)

Is it "a lack of relational sense of responsibility" in crisis response (state vs private sector vs public) or is it the wicked problem of power, class, social hierarchies, etc.?

"... ways of framing data and correlations that elicit a greater sense of responsibility and commitment."

That could have a temporal component to it to position urgency, timescape, horizon, etc.

This critique addresses surveillance state concerns about glue-ing datasets together to form a broader understanding of aggregate social behavior without the necessary constraints/warnings about social contexts and discontinuity between data.

Skimmed the Ruppert paper, sadly doesn't engage with time and topologies.

Beyond this quote, Chandler (in engaging crisis/disaster scenarios) argues that Big Data may be more appropriately framed as community reflexive knowledge than causal knowledge. That's an interesting idea.

*"Thus, It would be more useful to see Big Data as reflexive knowledge rather than as causal knowledge. Big Data cannot help explain global warming but it can enable individuals and household to measure their own energy consumption through the datafication of household objects and complex production and supply chains. Big Data thereby datafies or materialises an individual or community’s being in the world. This reflexive approach works to construct a pluralised and multiple world of self-organising and adaptive processes. The imaginary of Big Data is that the producers and consumers of knowledge and of governance would be indistinguishable; where both knowing and governing exist without external mediation, constituting a perfect harmonious and self-adapting system: often called ‘community resilience’. In this discourse, increasingly articulated by governments and policy-makers, knowledge of causal connections is no longer relevant as communities adapt to the real-time appearances of the world, without necessarily understanding them."

"Rather than engaging in external understandings of causality in the world, Big Data works on changing social behaviour by enabling greater adaptive reflexivity. If, through Big Data, we could detect and manage our own biorhythms and know the effects of poor eating or a lack of exercise, we could monitor our own health and not need costly medical interventions. Equally, if vulnerable and marginal communities could ‘datafy’ their own modes of being and relationships to their environments they would be able to augment their coping capacities and resilience without disasters or crises occurring. In essence, the imaginary of Big Data resolves the essential problem of modernity and modernist epistemologies, the problem of unintended consequences or side-effects caused by unknown causation, through work on the datafication of the self in its relational-embeddedness.42 This is why disasters in current forms of resilience thinking are understood to be ‘transformative’: revealing the unintended consequences of social planning which prevented proper awareness and responsiveness. Disasters themselves become a form of ‘datafication’, revealing the existence of poor modes of self-governance."*

Downloaded Chandler paper. Cites Meier quite a bit.