Category Archives: data analysis

History of complexity science

Here’s an interesting infographic of the main concepts and thinkers in complexity science across time. Notice S. Kauffman is slated in the 1980s column, suggesting the graphic depicts when influential thinkers first make their marks. 

https://www.art-sciencefactory.com/complexity-map_feb09.html

Applying artificial intelligence for social good

This McKinsey article is an excellent overview of this more extensive article (3 MB PDF) enumerating the ways in which varieties of deep learning can improve existence. Worth a look.

The articles cover the following:

  • Mapping AI use cases to domains of social good
  • AI capabilities that can be used for social good
  • Overcoming bottlenecks, especially around data and talent
  • Risks to be managed
  • Scaling up the use of AI for social good

Algorithm brings whole-brain simulation within reach

An improvement to the Neural Simulation Tool (NEST) algorithm, the primary tool of the Human Brain Project, expanded the scope of brain neural data management (for simulations) from the current 1% of discrete neurons (about the number in the cerebellum) to 10%. The NEST algorithm can scale to store 100% of BCI-derived or simulated neural data within near-term reach as supercomputing capacity increases. The algorithm achieves its massive efficiency boost by eliminating the need to explicitly store as much data about each neuron’s state.

Abstract of Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Source: http://www.kurzweilai.net/new-algorithm-will-allow-for-simulating-neural-connections-of-entire-brain-on-future-exascale-supercomputers

Recording data from one million neurons in real time

Given the human brain’s approximately 80 billion neurons, it would take tens of thousands of these devices to record a substantial volume of neuron-level activities. Still, this is a remarkable achievement.

The system would simultaneously acquire data from more than 1 million neurons in real time. It would convert the spike data (using bit encoding) and send it via an effective communication format for processing and storage on conventional computer systems. It would also provide feedback to a subject in under 25 milliseconds — stimulating up to 100,000 neurons.

Monitoring large areas of the brain in real time. Applications of this new design include basic research, clinical diagnosis, and treatment. It would be especially useful for future implantable, bidirectional BMIs and BCIs, which are used to communicate complex data between neurons and computers. This would include monitoring large areas of the brain in paralyzed patients, revealing an imminent epileptic seizure, and providing real-time feedback control to robotic arms used by quadriplegics and others.

Source: http://www.kurzweilai.net/recording-data-from-one-million-neurons-in-real-time?utm_source=KurzweilAI+Weekly+Newsletter&utm_campaign=ef0a349adb-UA-946742-1&utm_medium=email&utm_term=0_147a5a48c1-ef0a349adb-282174293

Cambridge Analytica pilfered Facebook data to influence election

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Sophisticated, sometimes AI-enabled data analytics tools allow construction of individual personality profiles accurate enough to support targeted manipulation of individuals’ perceptions and actions. 

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Last night Facebook announced bans against Cambridge Analytica, its parent company and several individuals for allegedly sharing and keeping data that they had promised to delete. This data reportedly included information siphoned from hundreds of thousands of Amazon Mechanical Turkers who were paid to use a “personality prediction app” that collected data from them and also anyone they were friends with — about 50 million accounts. That data reportedly turned into information used by the likes of Robert Mercer, Steve Bannon and the Donald Trump campaign for social media messaging and “micro-targeting” individuals based on shared characteristics.

 

https://www.engadget.com/2018/03/17/facebook-cambridge-analytica-data-analysis-chris-wylie/?sr_source=Facebook 

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Next discussion meeting Apr 2: Brain-Computer Interface, now and future

During our next discussion meeting, we’ll explore the status, future potential, and human implications of neuroprostheses–particularly brain-computer interfaces. If you are local to Albuquerque, check our Meetup announcement to join or RSVP. The announcement text follows.

Focal questions

What are neuroprostheses? How are they used now and what may the future hold for technology-enhanced sensation, motor control, communications, cognition, and other human processes?

Resources (please review before the meeting)

Primary resources
• New Brain-Computer Interface Technology (video, 18 m)
https://www.youtube.com/watch?v=CgFzmE2fGXA
• Imagining the Future: The Transformation of Humanity (video, 19 m)
https://www.youtube.com/watch?v=7XrbzlR9QmI
• The Berlin Brain-Computer Interface: Progress Beyond Communication and Control (research article, access with a free Frontiers account)
https://www.frontiersin.org/articles/10.3389/fnins.2016.00530/full
• The Elephant in the Mirror: Bridging the Brain’s Explanatory Gap of Consciousness (research article)
https://www.frontiersin.org/articles/10.3389/fnsys.2016.00108/full

Other resources (recommend your own in the comments!)

• DARPA implant (planned) with up to 1 million neural connections (short article)
https://www.darpa.mil/news-events/2015-01-19

Extra Challenge: As you review the resources, think of possible implications from the perspectives of the other topics we’ve recently discussed:
• the dilemma of so much of human opinion and action deriving from non-conscious sources
• questions surrounding what it means to ‘be human’ and what values we place on our notions of humanness (e.g., individuality and social participation, privacy, ‘self-determination’ (or the illusion thereof), organic versus technologically enhanced cognition, etc.)

A dive into the black waters under the surface of persuasive design

A Guardian article last October brings the darker aspects of the attention economy, particularly the techniques and tools of neural hijacking, into sharp focus. The piece summarizes some interaction design principles and trends that signal a fundamental shift in means, deployment, and startling effectiveness of mass persuasion. The mechanisms reliably and efficiently leverage neural reward (dopamine) circuits to seize, hold, and direct attention toward whatever end the designer and content providers choose.

The organizer of a $1,700 per person event convened to show marketers and technicians “how to manipulate people into habitual use of their products,” put it baldly.

subtle psychological tricks … can be used to make people develop habits, such as varying the rewards people receive to create “a craving”, or exploiting negative emotions that can act as “triggers”. “Feelings of boredom, loneliness, frustration, confusion and indecisiveness often instigate a slight pain or irritation and prompt an almost instantaneous and often mindless action to quell the negative sensation”

Particularly telling of the growing ethical worry are the defections from social media among Silicon Valley insiders.

Pearlman, then a product manager at Facebook and on the team that created the Facebook “like”,  … confirmed via email that she, too, has grown disaffected with Facebook “likes” and other addictive feedback loops. She has installed a web browser plug-in to eradicate her Facebook news feed, and hired a social media manager to monitor her Facebook page so that she doesn’t have to.
It is revealing that many of these younger technologists are weaning themselves off their own products, sending their children to elite Silicon Valley schools where iPhones, iPads and even laptops are banned. They appear to be abiding by a Biggie Smalls lyric from their own youth about the perils of dealing crack cocaine: never get high on your own supply.

If you read the article, please comment on any future meeting topics you detect. I find it a vibrant collection of concepts for further exploration.

Neural responses to media a strong predictor of friendship

“The findings revealed that  similarity was strongest among friends, and this pattern appeared to manifest across brain regions involved in emotional responding, directing one’s attention and high-level reasoning. Even when the researchers controlled for variables, including left-handed- or right-handedness, age, gender, ethnicity, and nationality, the similarity in neural activity among friends was still evident. The team also found that fMRI response similarities could be used to predict not only if a pair were friends but also the social distance between the two.”

https://medicalxpress.com/news/2018-01-brain-reveals-friends-similar-neural.html