31 Matching Annotations
  1. Last 7 days
    1. i feel for for tool builders that are serious about building useful software interoperability can actually be a huge 00:45:22 spoon uh to their success um it'll make easier to acquire users it will make it easier to help users embed your own tool in their workflows um you may be also losing some users but 00:45:34 that's okay i guess because it'll create sustainable pressure to you for you to focus on an audience well and build really really useful services for them and if you do that they also won't leave as easily

      I agree. I think companies that allow their users to take their data and run when they want to just create trust. Gone are the days when users automatically thought companies had their best interests at heart, as compared with current-day surveillance capitalists.

  2. May 2021
  3. Apr 2021
  4. Mar 2021
    1. The scholars Nick Couldry and Ulises Mejias have called it “data colonialism,” a term that reflects our inability to stop our data from being unwittingly extracted.

      I've not run across data colonialism before.

  5. Feb 2021
  6. Jan 2021
    1. The ad lists various data that WhatsApp doesn’t collect or share. Allaying data collection concerns by listing data not collected is misleading. WhatsApp doesn’t collect hair samples or retinal scans either; not collecting that information doesn’t mean it respects privacy because it doesn’t change the information WhatsApp does collect.

      An important logical point. Listing what they don't keep isn't as good as saying what they actually do with one's data.

  7. Oct 2020
    1. Legislation to stem the tide of Big Tech companies' abuses, and laws—such as a national consumer privacy bill, an interoperability bill, or a bill making firms liable for data-breaches—would go a long way toward improving the lives of the Internet users held hostage inside the companies' walled gardens. But far more important than fixing Big Tech is fixing the Internet: restoring the kind of dynamism that made tech firms responsive to their users for fear of losing them, restoring the dynamic that let tinkerers, co-ops, and nonprofits give every person the power of technological self-determination.
  8. Sep 2020
    1. Facebook ignored or was slow to act on evidence that fake accounts on its platform have been undermining elections and political affairs around the world, according to an explosive memo sent by a recently fired Facebook employee and obtained by BuzzFeed News.The 6,600-word memo, written by former Facebook data scientist Sophie Zhang, is filled with concrete examples of heads of government and political parties in Azerbaijan and Honduras using fake accounts or misrepresenting themselves to sway public opinion. In countries including India, Ukraine, Spain, Brazil, Bolivia, and Ecuador, she found evidence of coordinated campaigns of varying sizes to boost or hinder political candidates or outcomes, though she did not always conclude who was behind them.
  9. Aug 2020
  10. Jul 2020
    1. One of these semiotizing processes is the extraction, interpretation and reintegration of web data from and into human subjectivities.

      Machine automation becomes another “subjectivity” or “agentivity”—an influential one, because it is the one filtering and pushing content to humans.

      The means of this automated subjectivity is feeding data capitalism: more content, more interaction, more behavioral data produced by the users—data which is then captured (“dispossessed”), extracted, and transformed into prediction services, which render human behavior predictable, and therefore monetizable (Shoshana Zuboff, The Age of Surviellance Capitalism, 2019).

  11. Jun 2020
    1. Starr, T. N., Greaney, A. J., Hilton, S. K., Crawford, K. H., Navarro, M. J., Bowen, J. E., Tortorici, M. A., Walls, A. C., Veesler, D., & Bloom, J. D. (2020). Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding [Preprint]. Microbiology. https://doi.org/10.1101/2020.06.17.157982

  12. May 2020
  13. Apr 2020
    1. Google's move to release location data highlights concerns around privacy. According to Mark Skilton, director of the Artificial Intelligence Innovation Network at Warwick Business School in the UK, Google's decision to use public data "raises a key conflict between the need for mass surveillance to effectively combat the spread of coronavirus and the issues of confidentiality, privacy, and consent concerning any data obtained."
  14. Nov 2019
    1. Google has confirmed that it partnered with health heavyweight Ascension, a Catholic health care system based in St. Louis that operates across 21 states and the District of Columbia.

      What happened to 'thou shalt not steal'?

    1. Speaking with MIT Technology Review, Rohit Prasad, Alexa’s head scientist, has now revealed further details about where Alexa is headed next. The crux of the plan is for the voice assistant to move from passive to proactive interactions. Rather than wait for and respond to requests, Alexa will anticipate what the user might want. The idea is to turn Alexa into an omnipresent companion that actively shapes and orchestrates your life. This will require Alexa to get to know you better than ever before.

      This is some next-level onslaught.

  15. Sep 2019
  16. Jul 2019
    1. In contrast to such pseudonymous social networking, Facebook is notable for its longstanding emphasis on real identities and social connections.

      Lack of anonymity also increases Facebook's ability to properly link shadow profiles purchased from other data brokers.

  17. Nov 2018
    1. The Chinese place a higher value on community good versus individual rights, so most feel that, if social credit will bring a safer, more secure, more stable society, then bring it on
  18. Aug 2018
    1. However, with these big data collections, the focus becomes not the individu-al’s behaviour but social and economic insecurities, vulnerabilities and resilience in relation to the movement of such people. The shift acknowledges that what is surveilled is more complex than an individual person’s movements, communica-tions and actions over time.

      The shift from INGO emergency response/logistics to state-sponsored, individualized resilience via the private sector seems profound here.

      There's also a subtle temporal element here of surveilling need and collecting data over time.

      Again, raises serious questions about the use of predictive analytics, data quality/classification, and PII ethics.

    2. Andrejevic and Gates (2014: 190) suggest that ‘the target becomes the hidden patterns in the data, rather than particular individuals or events’. National and local authorities are not seeking to monitor individuals and discipline their behaviour but to see how many people will reach the country and when, so that they can accommodate them, secure borders, and identify long- term social out-looks such as education, civil services, and impacts upon the host community (Pham et al. 2015).

      This seems like a terribly naive conclusion about mass data collection by the state.

      Also:

      "Yet even if capacities to analyse the haystack for needles more adequately were available, there would be questions about the quality of the haystack, and the meaning of analysis. For ‘Big Data is not self-explanatory’ (Bollier 2010: 13, in boyd and Crawford 2012). Neither is big data necessarily good data in terms of quality or relevance (Lesk 2013: 87) or complete data (boyd and Crawford 2012)."

    3. as boyd and Crawford argue, ‘without taking into account the sample of a data set, the size of the data set is meaningless’ (2012: 669). Furthermore, many tech-niques used by the state and corporations in big data analysis are based on probabilistic prediction which, some experts argue, is alien to, and even incom-prehensible for, human reasoning (Heaven 2013). As Mayer-Schönberger stresses, we should be ‘less worried about privacy and more worried about the abuse of probabilistic prediction’ as these processes confront us with ‘profound ethical dilemmas’ (in Heaven 2013: 35).

      Primary problems to resolve regarding the use of "big data" in humanitarian contexts: dataset size/sample, predictive analytics are contrary to human behavior, and ethical abuses of PII.

  19. Mar 2017
    1. You can delete the data. You can limit its collection. You can restrict who sees it. You can inform students. You can encourage students to resist. Students have always resisted school surveillance.

      The first three of these can be tough for the individual faculty member to accomplish, but informing students and raising awareness around these issues can be done and is essential.

  20. Oct 2016
  21. Jul 2016