My Brave Ad Income

I have been following and participating in the Brave Internet program (ad blocking browser and ad-related services). My idealistic way of explaining the Brave program is that it provides the opportunity to protect user privacy while providing resources to content and service providers. There are a lot of assumptions in the model so label it as idealistic at present.

Brave just added the final component of the model – users can allow ads provided through Brave to be displayed and be compensated for viewing (in theory) these ads. Brave takes a cut of the funds provided by those who purchase the ads and Brave does not collect user data when displaying the ads. The content/service consumers is compensated by using the Brave ad model instead of existing ad models.

Last month I earned 6.1 BAT (presently valued at $2.04) for viewing ads through Brave. I used the lowest ad rate (2 per hour) and I could have set this higher. I also spent far more time online, but my Brave account is attached to my desktop computer and I do not accumulate BAT when using my laptop, tablet, or phone even though I might use the Brave browser on these other devices. Brave has yet found at a way to integrate accounts and the compensation plan also does not apply with tablets or phones. At this point.

I should also say that I cannot collect my $2.04 at this point, but this is supposedly coming. At present, I am just adding my income to the amount I have designated to support content creators.

Here is the biggest problem I see with the Brave model. I fear that most users will simply use the model to block ads and collect BAT for viewing Brave ads. One of the first “opportunities” Brave provided was for users to put in real model that was converted into BAT (a cryptocurrency) and the amount of this stash that was allocated per month would be distributed among the content/service providers that registered with Brave. I put in $50 as my investment in the experiment. I did register my domain (https://learningaloud.com) as part of this experiment. Brave provides no data on how many Brave users are also contributors. I am guessing not many so far.

Brave is great at protecting the privacy of users, BUT to this point it has protected producers only through voluntary contributions. Brave is in a position to do more. It would be as easy as splitting the ad revenue generated by the ads provided through Brave among itself, content creators, and consumers. Consumers could still make personal contributions. I just see this company advancing beyond privacy protection until it does a better job of including all of the parties involved in use of Internet resources.

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Student prep for dealing with misinformation is no longer effective

Fact Check

This article from the Chronicle of Higher Education concludes that the approach taken to prepare students to identify misinformation online is no longer effective. The authors suggest that popular strategies typically involve providing students a list of things that can look for within the content they are reading and they suggest that these red flags are too easy to eliminate should a content creator be serious about misinformation. They conclude that it is necessary to go beyond the content under consideration.

The necessary approach is to think like a “fact checker”. Open a couple of extra tabs and read laterally. Test facts offered by searching for other sources. Fact checking has become a part of the political scene as news sources identify a claim and then offer evidence from other sources that either verify or refute the claim.

What should be fact checked? I would think any claim that is crucial to the position being taken. I can imagine a situation in which a white board is used to display a web page. Students might then read and highlight core claims made in the article that is displayed. Students might then use their own devices to fact check these claims, save the sources, and paraphrase the critical material from these sources.

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Creative Commons Image Seach

I recently explained how you can assign creative commons licenses within Flickr and search for Flickr images offered under a CC arrangement. Now I learn that the Creative Commons web site has developed its own search engine for finding CC images within Flickr and several other image collection and sharing sites (TechCrunch).

To use this search site, visit the Creative Commons page and find the icon for image search which appears at the top of the page (first image). This icon opens a page providing access to the search engine (second image).

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The ENIAC girls vanish

Female coder

I don’t think I have ever recommended a chapter in a book and I understand that it is not very practical to do so, but I found Clive Thompson’s chapter “The ENIAC girls vanish” the best explanation of gender imbalance in tech that I have encountered. This chapter is from Thompson’s book – Coders: The making of a new tribe and the remaking of the world.

The title is a reference to the early dominance of female coders and the chapter traces the history of the proportion of women working as coders and the factors responsible for changes. I cannot do justice to the complexity of this issue, but I will attempt to identify a couple of issues I found to be interesting.

In the beginning, men did hardware and women did software. Software despite the actual challenges of programming primitive machines was considered pretty much a secretarial task. As more and more programmers were needed and as wages increased more and more males were drawn into the field.

Thompson spends considerable time explaining changes in the makeup of college computer science students. Enrollment in CS programs was primarily male – white and Asian. Computer science faculty members were not oblivious to the lack of diversity of their students and made efforts to understand why. Thompson explains that makes had an advantage in early courses because of previous coding experiences. These were not kids who had taken CS in high school and this was at a time when having a computer at home was expensive. Early computers – TRS80s, Apple IIs – had limited software of interest to adolescents, but those who had access and were interested learned to program them to explore. Males thus came to college with experience and often dominated the initial courses discouraging the women who took the courses from scratch. The women who stuck it out ended up doing just as well in later courses. To address this issue, the CS programs decreased the size of intro classes and tried to offer greater individual attention in introductory courses.

Thompson then argues that CS became a victim of its own success. The visibility of the financial opportunities in developing software especially for online functions resulted in students swamping CS programs. The opportunities not only increased the number of interested students, but also made it far more difficult for higher ed to recruit and retain faculty members. Classes again ballooned in size and programs to shepherd beginning students were dropped. Getting through the early classes again was heavily biased by experience before these classes and those willing to compete to advance within these programs. This situation led to a decline in females entering and completing CS programs. The stereotype of successful programmers/entrepreneurs perpetuated in media also put off competent women. There have been some recent improvements, but the trend has yet to revert to what it was even 20 years ago.

Solutions? Thompson makes a compelling case that the talent for coding is widely distributed if individuals have the opportunities to develop this talent. It would seem that the issue is at what level should the money be spent to develop talent and what level of proficiency should be expected at the next level. Would wide availability of a CS course in high school be enough? Should higher education be funded at a level necessary to start students from scratch?

I have been trying to locate something else Thompson has written on this topic I could offer. I found this interview with Thompson that you may find of some use.

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Teachers fail to engage students with creativity tools

Common Sense has released its annual report on K-12 education and there is plenty in this report for those interested in technology integration. Concerns listed include issues of digital citizenship, equitable access for the use of technology from home. helpful professional development, and technology as a distraction in the classroom.

One specific issue that caught my attention was teacher concern for their opportunity to allow students to use technology in what were described as creative ways.

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Text Compactor

Leslie Fisher recently posted a link to a text compactor. She described the site as a way to simplify text.

I just completed writing a piece on the causes of adolescent screen time so I thought I would give it a try. I first attempted to have the compactor reduce my 4500-word project and that proved to be beyond the capacity of the site. I recently posted a section of this same project that focused on surveillance capitalism which was 1100 or so words long as a blog post so I tried this shorter piece. At the bottom of this post, the summary service generated is included (reduced to 33% of the original length).

Shortened summary.

I interpret the phrase as a way to describe the business model of most social media sites. These sites are free in that users do not pay a subscription fee. The sites make income to cover the costs of infrastructure, employee salaries, and to make a profit by collecting data about those who use the sites and either then target personal ads assumed to be attractive to users by using these data or by selling these data to other businesses. Social media sites explain their business models in agreements they ask users to approve before using the sites, but the length of these agreements limits the proportion of users who actually review the terms users have been willing to deem acceptable and the vagueness of the language as it relates to how users see themselves using the sites limit user understanding of how their data are being used. Zuboff, 2019).

Much of the negative connotation associated with surveillance capitalism is based on the techniques some online companies use to collect user information to improve the appeal of their ads and to increase of the value of personal information these companies can sell as a resource.

To collect as much and as varied data as are possible, sites seek to encourage heavy and exclusive use. Put another way, to generate a business advantage, sites are motivated to use strategies that generate heavy use. Content that offers these stimuli, whether prioritized by online services or highlighted by any of us as content creators or at least by any of us who share such content, attracts viewers and increases the collection of information about these users that is a byproduct of their online attention. I will explore this issue further in my discussion of psychological processes.

Online sites can feed these personal biases in two different ways. Some social media sites allow users to prioritize the content offered by certain individuals. Systems that learn about us and use this information to prioritize certain information over other information can also feed existing biases. A site developed by Duck Duck Go (a search engine that claims to be neutral) explains how bias due to the filter bubble can be investigated (Duck Duck Go – https://spreadprivacy.com/google-filter-bubble-study/).

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