68 Matching Annotations
  1. Sep 2019
    1. various institutions have varying levels of resources to serve their students.

      Digital Redlining is a broad problem with society at large but has specific impacts in higher education that are often not related or realized.

    2. Neil Selwyn

      Neil Selwyn is a professor in the Faculty of Education, Monash University. His research and teaching focuses on the place of digital media in everyday life, and the sociology of technology (non)use in educational settings

  2. Jul 2019
    1. helplessness

      During our 1st #DigPINS week on Digital Identity many expressed concerns around a lack of control in digital spaces. Perhaps something similar happening here?

    2. all the things that a teenager could get into in an hour on the internet

      Concerns listed in this paragraph and the next seem to fall into three categories: exposure to inappropriate content, abuse by other people, and negative effects from interfaces and devices themselves.

  3. Jun 2019
    1. Then, the question becomes

      Or perhaps the question is if its training data itself is flawed - from the MIT Technology Review article AI is sending people to jail—and getting it wrong

      "....You may have already spotted the problem. Modern-day risk assessment tools are often driven by algorithms trained on historical crime data.

      As we’ve covered before, machine-learning algorithms use statistics to find patterns in data. So if you feed it historical crime data, it will pick out the patterns associated with crime. But those patterns are statistical correlations—nowhere near the same as causations. If an algorithm found, for example, that low income was correlated with high recidivism, it would leave you none the wiser about whether low income actually caused crime. But this is precisely what risk assessment tools do: they turn correlative insights into causal scoring mechanisms.

      Now populations that have historically been disproportionately targeted by law enforcement—especially low-income and minority communities—are at risk of being slapped with high recidivism scores. As a result, the algorithm could amplify and perpetuate embedded biases and generate even more bias-tainted data to feed a vicious cycle. Because most risk assessment algorithms are proprietary, it’s also impossible to interrogate their decisions or hold them accountable."

    2. Machine behaviour

      This appears to be a push from MIT to develop a new field of study. Besides this article there were several other more promotional articles published as well as a YouTube channel established that has interviews with several of the authors.

    3. Computer Fraud and Abuse Act in the United States

      From Wikipedia

      The Computer Fraud and Abuse Act (CFAA) is a United States cybersecurity bill that was enacted in 1984 as an amendment to existing computer fraud law (18 U.S.C. § 1030), which had been included in the Comprehensive Crime Control Act of 1984. The law prohibits accessing a computer without authorization, or in excess of authorization.[1] Prior to computer-specific criminal laws, computer crimes were prosecuted as mail and wire fraud, but the applying law was often insufficient.

      In January 2015 Barack Obama proposed expanding the CFAA and the RICO Act in his Modernizing Law Enforcement Authorities to Combat Cyber Crime proposal.[4] DEF CON organizer and Cloudflare researcher Marc Rogers, Senator Ron Wyden, and Representative Zoe Lofgren have stated opposition to this on the grounds it will make many regular Internet activities illegal, and moves further away from what they were trying to accomplish with Aaron's Law.

    4. Ethical considerations such as these need careful oversight and standardized frameworks.

      I can't help but wonder who will be the players who make those decisions? And what about the division between theory and practice? From Aeon - Cheeseburger Ethics

      "Ethicists do not appear to behave better. Never once have we found ethicists as a whole behaving better than our comparison groups of other professors, by any of our main planned measures. But neither, overall, do they seem to behave worse. (There are some mixed results for secondary measures.) For the most part, ethicists behave no differently from professors of any other sort – logicians, chemists, historians, foreign-language instructors."

    5. Indeed, no behaviour is ever fully separable from the environmental data on which that agent is trained or developed

      Nurture FTW

    6. For example, questions include to what extent and what ways are governments using machine intelligence to alter the nature of democracy, political accountability and transparency, or civic participation.
    7. whether the matching algorithms that are used for online dating alter the distributional outcomes of the dating process

      One example from Wired

      When it comes to real humans on real dating apps, that algorithmic bias is well documented. OKCupid has found that, consistently, black women receive the fewest messages of any demographic on the platform. And a study from Cornell found that dating apps that let users filter matches by race, like OKCupid and the League, reinforce racial inequalities in the real world. Collaborative filtering works to generate recommendations, but those recommendations leave certain users at a disadvantage.

    8. Bayesian state

      Recursive Bayesian estimation - Wikipedia

      A Bayes filter is an algorithm used in computer science for calculating the probabilities of multiple beliefs to allow a robot to infer its position and orientation.

      In a simple example, a robot moving throughout a grid may have several different sensors that provide it with information about its surroundings. The robot may start out with certainty that it is at position (0,0). However, as it moves farther and farther from its original position, the robot has continuously less certainty about its position; using a Bayes filter, a probability can be assigned to the robot's belief about its current position, and that probability can be continuously updated from additional sensor information.

    9. These dynamics are ultimately driven by the success of institutions—such as corporations, hospitals, municipal governments and universities—that build or use AI.

      The intersection of AI and capitalism

    10. ethology, identified four complementary dimensions of analysis

      Tinbergen's four questions - Wikipedia

      Tinbergen's four questions, named after Nikolaas Tinbergen and based on Aristotle's four causes, are complementary categories of explanations for behaviour. These are also commonly referred to as levels of analysis.[1] It suggests that an integrative understanding of behaviour must include both a proximate and ultimate (functional) analysis of behaviour, as well as an understanding of both phylogenetic/developmental history and the operation of current mechanisms

    11. Nikolaas Tinbergen

      Early work in Instinct - from Wikipedia

      In 1951 Tinbergen's The Study of Instinct was published. Behavioural ecologists and evolutionary biologists still recognise the contribution this book offered the field of behavioural science studies. The Study of Instinct summarises Tinbergen's ideas on innate behavioural reactions in animals and the adaptiveness and evolutionary aspects of these behaviours. By behaviour, he means the total movements made by the intact animal; innate behaviour is that which is not changed by the learning process. The major question of the book is the role of internal and external stimuli in controlling the expression of behaviour

    12. are predominantly the same scientists who have created the agents themselves

      Conflict of interest?

    13. Herbert Simon

      From Wikipedia

      Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American economist, political scientist and cognitive psychologist, whose primary research interest was decision-making within organizations and is best known for the theories of "bounded rationality" and "satisficing". He received the Nobel Prize in Economics in 1978 and the Turing Award in 1975. His research was noted for its interdisciplinary nature and spanned across the fields of cognitive science, computer science, public administration, management, and political science. He was at Carnegie Mellon University for most of his career, from 1949 to 2001.

    1. intrinsicconnectivitynetworks

      From Behavioral Interpretations of Intrinsic Connectivity Networks

      The term “intrinsic connectivity network” expands upon the concept of resting state networks to include the set of large-scale functionally connected brain networks that can be captured in either resting state or task-based neuroimaging data.

      Only skimmed

    2. thesefeaturesenablehighlocalandglobalefficiencyatrelativelylowcost

      Though this game from Nicky Case is looking at networks between people rather than networks in the brain - it is a fun interactive way to understand networks. Small world network structure is covered on module #5.

    3. Minimizationofcostisachievedbydividingthecortexintoanatomicallylocalizedmodules,composedofdenselyinterconnectedregionsornodes
    4. Cattell–Horn–Carrolltheory
  4. May 2019
    1. always

      I'm leery of "always's" and "never's" and sort of went down the rabbit hole chasing this one. It does seem well established but at the same time not uncontroversial or uncontested. There seems to be hints of racism and injustice.

      Though I only skimmed it I found this article to propose a kind of third way and distinguishes that there is a difference between g as a psychometric construct (where the positive manifold is present) and g as a psychological construct where the controversies arise.

    2. ofindividualdifferences

      Differences between individuals (I think) or within individuals?

    3. CharlesSpearman

      Spearman on g from Wikipedia quoted from Deary, I. J.; Lawn, M.; Bartholomew, D. J. (2008). ""A conversation between Charles Spearman, Godfrey Thomson, and Edward L. Thorndike: The International Examinations Inquiry Meetings 1931-1938": Correction to Deary, Lawn, and Bartholomew (2008)". History of Psychology. 11 (3): 163. doi:10.1037/1093-4510.11.3.163.

      When asked what G is, one has to distinguish between the meanings of terms and the facts about things. G means a particular quantity derived from statistical operations. Under certain conditions the score of a person at a mental test can be divided into two factors, one of which is always the same in all tests, whereas the other varies from one test to another; the former is called the general factor or G, while the other is called the specific factor. This then is what the G term means, a score-factor and nothing more. But this meaning is sufficient to render the term well defined so that the underlying thing is susceptible to scientific investigation; we can proceed to find out facts about this score-factor, or G factor. We can ascertain the kind of mental operations in which it plays a dominant part as compared with the other or specific factor. And so the discovery has been made that G is dominant in such operations as reasoning, or learning Latin; whereas it plays a very small part indeed in such operation (sic) as distinguishing one tone from another. . . G tends to dominate according as the performance involves the perceiving of relations, or as it requires that relations seen in one situation should be transferred to another. . . . On weighing the evidence, many of us used to say that this G appears to measure some form of mental energy. But in the first place, such a suggestion is apt to invite needless controversy. This can be avoided by saying more cautiously that G behaves as if it measured an energy. In the second place, however, there seems to be good reason for changing the concept of energy to that of "power" (which, of course, is energy or work divided by time). In this way, one can talk about mind power in much the same manner as about horse power. . . . . . .G is in the normal course of events determined innately; a person can no more be trained to have it in higher degree than he can be trained to be taller. (pp. 156 –157).

    4. AronK.Barbey

      From Wikipedia

      Aron Keith Barbey (born January 6, 1977) is an American cognitive neuroscientist, who investigates the neural architecture of human intelligence. Barbey is the Emanuel Donchin Professorial Scholar of Psychology and an Associate Professor of Psychology, Neuroscience, and Bioengineering at the University of Illinois. He is Director of the Decision Neuroscience Laboratory at the Beckman Institute for Advanced Science and Technology, and founding director of the Center for Brain Plasticity at the Beckman Institute, where he leads the Intelligence, Learning, and Plasticity (ILP) Initiative.

  5. Jan 2019
    1. the LMS is no match for the wideness of the Internet

      Agreed! But I'm not so sure that wideness is always good for learning either. I want both and agency over which is used when.

    2. the LMS convinced us that teaching online was not only possible, it was easy

      I don't blame the LMS here - I blame people, the stories that they tell, and a long history of behavioral edpsych behind educational technology as a whole.

    3. The LMS was a mistake because it was premature.

      This is so often the case with technology systems. It is born out of the tech/business culture and silicon valley mindset. "Move fast and break things" right?

      But part of me does not want to fault it for being premature so much as I want to fault it for lack of imagination and worse an inability to imagine over time.

    4. mistake

      I don't know. I'm very conflicted here. I agree with the whole paragraph and part of me wants to even take it further to talk about the way the LMS is platform and how all platforms concentrate power in subtle ways that users (who in this case are students) can't always see.

      On the other hand part of me feels like this is somewhat harsh. The LMS does have some merit when it comes to finding a starting place, a low hanging fruit, for teaching online. It can also serve as a protected backchannel in some situations if working with students who would be vulnerable in open networks or in platforms (designed for consumers) that may have predatory practices in the way of advertising or data extraction.

      So yeah... conflicted [thinky face]

  6. Nov 2018
  7. Jul 2018
    1. The more nebulous I was about my expectations

      I love that the expectations were collaboratively created with the students - take a moment to check out this link

    2. —Miranda Dean, undergraduate student, In ‘What an Open Pedagogy Course Taught Me About Myself

      This post is soooooo good. Take a moment to read this when you get a chance. Student voice in this post is really amazing.

    3. When we stop judging students they stop judging and censoring themselves. They begin to actually learn.

      <3

    4. participation is an individual choice

      Focus on ownership and agency of the learner

  8. Jan 2018
    1. Bryn Mawr Digital Competencies Framework

      I think the BMC Digital Competences are awesome!!!

  9. Oct 2017
    1. Digital education reshapes its subjects. The possibility of the ‘online version’ is overstated.

      I'm not sure I understand what is meant by this or how the two part of this point are related. How does digital education reshape its subjects? Are "subjects" teachers or students or administrators or what? Doesn't all education reshape a person? What is this possibility that is spoken of in the second part? What if the "online version" is the only version... I'm just confused by this whole point.

    2. was reproduced

      I love that this was copied especially for the purpose of annotating. This is very interesting to me in terms of respecting the author and the open space to annotate.

  10. Jul 2017
    1. Slack may share Customer Data

      Questioning here:

      By "Customer Data" they are refering to #1 under "Information we collect and receive" where it states "Here are some examples of Customer Data (but keep in mind they are only examples and there may be others): messages (including those in channels and direct messages), pictures, videos, edits to messages or deleted messages, and other types of files. A user may also choose to enter information into their profile, such as first and last name, job, a photo and a phone number."

    2. As further explained below, Customer Data is controlled by the organization or other third party that created the team (the “Customer”). Where Slack collects or processes Customer Data, it does so on behalf of the Customer.

      I wonder what "controlled" means in this sentence? Interesting that they did not use the word "owned". According to this I have been both a customer and a user in different Slack teams but I'm not sure exactly how much more "control" I get as an owner. I suppose I get those analytic reports but it is not like I get access to messages in private channels or DMs.... so i find this a bit confusing.

  11. Apr 2017
    1. It is still possible to envisage behavioral science playing a part in the great social experiment of providing the kind of public education that nurtures the critical faculties of everyone in our society.

      ...

    2. the very existence of such companies tells us something important about the weight that unconscious influence

      Agreed

    3. It is impossible to test the claims of organizations such as Cambridge Analytica, since there can be no control group, only the kind of ambiguous observational data that can be attained in a very “noisy” environment.

      A statement like this concerns me because we don't even have access to the noisy data. This statement seems to write off the prospect that having transparency would give us something and that bothers me. It seems to state that the environment is so "noisy" that we would never be able to make sense of it. But the truth is that we don't know because we can't see the data or the context in which it was collected.

    4. But it is important to remember that this much-discussed video is a sales pitch.

      agreed

    5. It is either an empty boast or there is a disturbing story to be told about how they acquired this information.

      They can't have it both ways

    6. unpack the knowledge hidden in big data,” “design…choice architectures,” and “reduce noise in decision-making” (that is, to eliminate inconsistencies created by conflicting subjective judgments in organizations)
    7. But Facebook defended the research on the grounds that its users’ consent to their terms of service was sufficient to imply consent to such experiments.

      This makes me angry - this is not informed consent - no one reads the TOS

    8. When this came to light in 2014 it was generally seen as an unacceptable form of psychological manipulation
    9. If subjects are unaware of this unconscious influence, the freedom to resist it begins to look more theoretical than real.

      There it is again that unconscious bit

    10. for instance flashing smiley faces on a screen at a speed that makes them undetectable
    11. we need not rely on our faulty subjective judgments about what will make us happy

      instead we are to assume benevolence of a third party that will decide what will make us happy...

      ... le sigh

    12. Scores on these tests could be combined with enormous amounts of data from the user’s Facebook environment.

      Boom

    13. Their claim is that this form of influence, albeit often unconscious, is not manipulative or coercive because the possibility of a person choosing differently is not closed down

      I find this so troubling though... this is not free will or free choice. This is coercion at it's most basic.

    14. the potential for doing good through such means can be a kind of magic

      Alas that is the problem with moving to science before magic is understood... the fact that good magic and bad magic are two sides of the same coin is never fully grasped.

    15. Lewis supplies a consistently redemptive narrative, insisting that this new psychological knowledge permits us to compensate for human irrationality in ways that can improve human well-being

      Ummmm.... unless it is being sold the highest bidder...

    16. people regretted losses caused by their actions more than they regretted inaction that could have averted the loss

      Ah yes - we are biased toward action arn't we?

      I see something similar in the neturality illusion as well - if we don't say anything then we are not taking sides.

    17. emotions powerfully influence our intuitive analysis of probability and risk.

      Sorry but ... well Duh

    18. System One, which is fast and automatic, including instincts, emotions, innate skills shared with animals, as well as learned associations and skills; and System Two, which is slow and deliberative and allows us to correct for the errors made by System One.

      And is there a propensity for some folks toward more of one than the other? Can environment affect this....

      .... perhaps I need to just read the article ;-p

    19. If psychologists could possess a systematic understanding of these nonrational motivations they would have the power to influence the smallest aspects of our lives and the largest aspects of our societies.

      So what is the effect on democracy? What is the response from those that love consciousness and want to encourage rational thought?

    20. unconscious

      This seems to be the bit that is concerning to me. So much of this is unconscious. Unconscious consent, unconscious collection, unconscious analysis, unconscious filtering....

    21. inescapable

      This seems so broad to me yet I wonder to what lengths I would need to go to escape them... Perhaps documenting such and endeavor would shed light?

  12. Feb 2017
    1. Authority Is Constructed and Contextual

      This seems so important to me right now in terms of misinformation and "fake news" rhetoric abound.

  13. Oct 2016
    1. Why students who do well in high school bomb in college

      Just a reminder for students that are here annotating with the #fyschat project - tips and best practices on annotating in a public space can be found here https://hypothes.is/annotation-tips-for-students/

  14. Sep 2016
    1. we actually find ourselves at risk of losing our humanity.
    2. “Thorndike won and Dewey lost,”

      If this is true the best we can hope for is to upset the ideas of winning and losing.

      binary

      complexity

      see it

  15. Aug 2016
    1. computer labs

      Here I start wondering about the politics between IT, academic departments, and the library. Could a campus computer lab have different filter settings on a general computer lab, a discipline specific computer lab, and the computer lab in the library

    1. You can’t be an adaptive learner if you don’t know anything,

      I suppose this is true in the most absolute sense of things but how many of our students don't know anything when they come to us? All students know something. The key is to get them to connect what they are learning to what they already know.

    2. efficient

      When you see this word in relation to edtech beware. Look to replace with word with creativity instead.

      ~ my 2 cents

    1. Wherever you go in the world, you can pretty much guarantee that a good proportion of the people around you will be too busy checking their phones to look up and appreciate their surroundings.