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Twitter Reading Limit Risks Human Users to Curb AI Threat

Twitter has recently announced to limit the number of posts users can read per day, depending on their account status. The policy was announced by the chairman Elon Musk on 1 July 2023. According to Musk, this temporary measure can prevent data scraping and system manipulation by artificial intelligence companies and other entities that use Twitter’s data for their own purposes. He also assured the users that the platform will drop these limits once it has developed better ways to tackle such issues.

How Does Twitter Reading Limit Works?

The billionaire announced the new criteria for each type of Twitter users. Verified accounts, which are either granted by Twitter or purchased through the Twitter Blue subscription service, can read up to 10,000 posts per day. Unverified accounts can read up to 1,000 while new users can read up to 500 Tweets per day. New users mean the accounts that are created after this announcement i.e. 1 July.

These are revised numbers after Musk’s previous 2 attempts received heavy backlash. Initially, he tweeted that verified, unverified, and new users can only read up to 6000, 600, and 300 tweets per day, respectively.

In case users exceed their reading limit, they will see a message saying “Rate limit exceeded” and will not be able to view any more posts until the next day. Moreover, those who do not have a Twitter account are no longer be able to view any Tweets on the website.

The Price of Privacy

The new Twitter reading limit have caused frustration among users, with some being locked out of Twitter for the day after scrolling through several hundred tweets. On Saturday, thousands of users reported difficulties accessing the site and complained about the limitations.

The implementation of these restrictions had widespread effects, with over 7,500 users reporting problems, according to Downdetector, a website that tracks online outages. While this number is relatively small compared to Twitter’s global user base of over 200 million, the issue gained attention and caused hashtags like #TwitterDown, #ratelimitexceeded, and #WTFTwitter to trend in certain regions.

Several users, celebrities, journalists and activists have called it a violation of free speech and expression, which Musk tries to champion. They see it as another attempt to create a gated community for the elite, after putting a price tag on Blue Tick. Some take it as a severe sign of technical and financial problems at Twitter.

Many users have reported issues with accessing Twitter, such as missing timelines, disappearing followers and service outages. Musk has blamed these problems on AI scraping data and system overload, but critics have suggested that they may be caused by his vague decisions like laying off most of Twitter’s staff since taking over the company last year.

The policy has sparked a lot of backlash from several personalities who think he’s pushing his users away in pursuit of containing AI scraping.

Artificial Intelligence and Social Media

Musk has been vocal about his concerns regarding the misuse of Twitter data, particularly in training popular AI systems like ChatGPT, which generate human-like content using vast amounts of online information. He has been warning about the risks of AI for years, and he has not been shy about expressing his views on social media, interviews, and conferences. He has called AI “the biggest existential threat” to humanity, and he has urged for more regulation and oversight of the technology.

He believes that AI can outsmart and outperform humans in every domain unless its aligned with human values and goals. Besides his more extreme views, some of the concerns he raised about AI’s social and environmental impact are notable.

Data scraping by AI companies is an ethical as well as legal issue. It is the process of extracting data from websites or other sources using automated tools, such as bots, crawlers, or scrapers. Data scraping can be used for various purposes, such as market research, price comparison, sentiment analysis, content aggregation, and more. However, there are serious challenges and risks, especially when it is done by companies using the scraped data to train their algorithms or offer their services.

It is one of the reasons why there’s a frequent leak of someone’s personal information, such as names, addresses, phone numbers, password, or private images and videos. Similar incident happened to Facebook users 2 years ago. Rogue actors can use this data for identity theft, blackmail, phishing, spamming, or other malicious activities.

Moreover, AI companies consume a lot of resources, such as bandwidth, storage space, electricity, and computing power to scrape data. This in turn contributes to environmental issues, such as carbon emissions, or e-waste.

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