Snap, the parent company of Snapchat has announced new features to further protect kids between the age of 13-17 years from potential online risks. These features will begin to roll out in the coming weeks. The latest safeguards build on the protections that are already available to limit unwanted interactions or potentially risky contact on the platform.What will these features do?The new features are aimed to protect teens from being contacted by people they may not know in real life. They will also provide a more age-appropriate viewing experience on the content platform. Along with a new strike system and new detection technologies, these features will also enable more effective removal of accounts that may be trying to market and promote age-inappropriate content. “As a messaging platform for real friends, the goal is to help Snapchatters communicate with people that matter to them, and to ensure that the content they view on the app is informative, fun and age-appropriate,” the company said. What are new features?In-App Warnings: This feature will send a pop-up warning to a teen if someone tries to add them as a friend when they don’t share mutual contacts or the person isn’t in their contacts. The message will urge teens to carefully consider if they want to be in contact with this person. Stronger friending protections: Snapchat already requires 13-to-17-year-olds to have several mutual friends in common with another user before they can show up in Search results. The company is now raising the required number of friends needed to show up in search. Immediate banning of accounts: Snapchat does not allow harmful content such as sexual exploitation, pornography, violence, self-harm and misinformation on the platform. If an account is found engaging in this activity, it will be immediately banned. “Our latest features are thoughtful in-app features that are designed to empower teens to make smarter choices, and talk openly about staying safe online. We’re committed to making sure Snapchat is a place where you can be creative and stay safe and above all, the safety and well-being of our community in India, which includes over 200 million users, is our top priority,” said Uthara Ganesh, head public policy-South Asia at Snap.New tools for familiesIn addition to the new safeguards, Snap is also releasing new resources for families, which include an updated parents guide at parents.snapchat.com. The guide lists protections for teens, tools for parents and a new YouTube explainer series.

Localized data refers to information or content obtained from and restricted to access from a specific location. Data of this nature contains aggregated information that could provide businesses with insights into customer behavior and preferences of specific populations. On the other hand, Business Intelligence (BI) refers to methods and means by which companies facilitate data collection, collation, analysis and, presentation. However, no definition or concept of BI is complete without including the data and the quality of the data. For an international business, localized data is especially important to the quality of BI systems because of its peculiarity to the population of interest. However, countries are increasingly localizing data, citing security reasons. This article will explain how localized data impacts business, what they are used for, and how to harvest them with a location proxy. How Does Localized Data Impact Business Intelligence In business, data helps identify patterns and correlations that are not usually obvious. Based on the scope of data collection, data can be local or international. Local data originates from the home country of the business, while international data is obtained from foreign markets. Localized data is the type of data that businesses seek to obtain as part of an international data collection operation. With proper analysis and interpretation, this type of data can give businesses an edge in a business sphere that can seem crowded. That said, here are specific ways that Localized data can affect business intelligence: Improved accuracy of insights. Data informs insight, and accurate data means accurate insights. Localized data is the most accurate form of data obtainable on a population. For instance, any survey of a population can identify customer distribution, but localized data can accurately chart the distribution in a region. Specific cultural and regional relevance. Localized data can point to cultural beliefs and preferences affecting consumer behavior. For instance, an international fast-food business looking to operate in India might be aware of the general stance on beef consumption. However, localized data could help point out that the Hindus make up the vast majority of the population, thus ruling out beef-containing meals as a potentially nationally successful meal. Accurate assessment of expansion prospects. Businesses planning to expand into new markets can better assess the security of their position by using localized data. In this case, they can use localized data to understand local competition, determine demand and preferences, evaluate regulatory measures, and optimize the efficiency of their operations. Fairer analysis of global performance. Using localized data, businesses can assess the performance of products and services with more contextual knowledge. So they can make smarter decisions and develop strategically sound plans. How Web Scraping and Proxy Servers Help Localized Data Collection Localized data may frequently have geographical restrictions to prevent residents outside the region from gaining access. A web-scraping tool and a location proxy can help businesses work around these restrictions if they exist. The location proxy server receives the internet traffic from the computer collecting the data. Once received, it then forwards the traffic (in this case, a scraping request) to the target servers of the website. This means that the target website would recognize the traffic as originating from the location of the proxy server. On the other hand, after the target website receives the scraping request, the web scraper downloads the HTML contents of the site and extracts the needed data from within. In this way, the location proxy and web scraper complement one another to bypass geographical and IP restrictions on data and automatically retrieve them. Women using computers with cloud network How the Quality of Proxy Providers Affects Localized Data Collection A large pool of IP addresses and variability in locations within the pool are attractive features for business proxies. A location proxy provider with many addresses in many countries is beneficial for localized data collection in the following ways: Access to more locations. More variation in the countries means the business can access localized data from more locations if needed. Some proxy providers have access to over 150 countries. Such a proxy would allow its users to access data from a vast pool of locations, increasing the reach of their data collections. For instance, a business owner in the UK can extract information from a US website using a US proxy and vice versa. Efficient load distribution and scalability. Any proxy provider with many addresses allows users to rotate their proxies during data collection. However, the size of the address pool within a location can make rotations more efficient. A larger pool means that users do not have to reuse an address (and risk an IP block) very often. Conclusion There is no business intelligence without data, and the more accurate the data collected, the more valuable the intelligence obtained would be. Considering the importance of localized data to BI, businesses prioritize obtaining them, regardless of the obstacles or restrictions surrounding their acquisition. The result of this in the business world is that companies hire the best people, utilize the best technologies, and try to collect localized data. Web scraping and proxy providers work in tandem to make this possible. Any business looking to positively distinguish its performances from those of its competitors should be doing the same.

it’s become a veritable meme subgenre at this point: a photo of Linda Hamilton as The Terminator’s Sarah Connor, glaring into the camera, steely eyed, with some variant of the caption “Sarah Connor seeing you become friends with ChatGPT.” Our society has interpreted the sudden, dizzying rise of this new chatbot generation through the pop cultural lens of our youth. With it comes the sense that the straightforward “robots will kill us all” stories were prescient (or at least accurately captured the current vibe), and that there was a staggering naivete in the more forgiving “AI civil rights” narratives—famously epitomized by Star Trek’s Commander Data, an android who fought to be treated the same as his organic Starfleet colleagues. Patrick Stewart’s Captain Picard, defending Data in a trial to prove his sapience, thundered, “Your honor, Starfleet was founded to seek out new life: Well, there it sits! Waiting.” But far from being a relic of a bygone, more optimistic age, the AI civil rights narrative is more relevant than ever. It just needs to be understood in its proper context. There are understandable fears that seemingly naive narratives about AI or robots being “just like us” have only paved the way for the morally impoverished moment in which we now find ourselves. In this way of looking at things, we need more fear of AI in order to resist the exploitation we’re now faced with, surely. Thus, we need to retrench into the other AI narrative cliché: They’re here to kill us all. But analogizing ChatGPT or Google’s Bard to even embryonic forms of Skynet is priceless PR for tech companies, which benefit greatly from the “criti-hype” of such wild exaggerations. For example, during a 60 Minutes interview, Google vice president James Manyika remarked, “We discovered that with very few amounts of prompting in Bengali, [Bard] can now translate all of Bengali.” In his narration, CBS journalist Scott Pelley glossed this comment by saying “one Google AI program adapted on its own after it was prompted in the language of Bangladesh, which it was not trained to know”—suggesting that this learning was a potentially dangerous “emergent property” of Bard. But it also implied that Bard had no Bengali in its training data, when in fact it did. Such hyperbole, which portrays the algorithms as bordering on self-awareness, makes these tools seem far more capable than they really are. That, of course, hasn’t stopped some of my fellow nerds, reared on C-3PO and Data, from being all too eager to join the final frontier of civil rights battles—even when every other one remains woefully unfinished. So what’s the use in continuing to tell the happier “AI deserves civil rights” stories? After all, we’re a long way from boldly arguing for the rights of such beings in a Starfleet courtroom, and such stories might only further engender anthropomorphization, which only helps companies profit from tools that fall short even at their stated functions. Well, those stories might help us keep our priorities straight. Far from being a relic of a bygone, more optimistic age, the AI civil rights narrative is more relevant than ever. It just needs to be understood in its proper context. It’s easy to forget that, in fiction, the AI/robot is almost always a metaphor. Even in Star Trek: The Next Generation, Data and the androids like him were analogized to humanity’s ugly history of slavery—the grotesque dream of free labor that never questions, never fights back. This was equally evident in Ex Machina, a horror film about how an AI woman, built to be a classic “fembot,” liberates herself from a male tech baron who wants nothing more than to build a woman who loves to be abused. What we yearn for in machines is so often a reflection of what we yearn for in humanity, for good and ill, asking us what we really want. Stories of such yearnings also illustrate a key requirement for sapience: resistance to oppression. Such qualities take us back to the earliest forms of fiction that humans wove about the prospect of creating artificial life. Not just Karel Čapek’s 1921 Rossum’s Universal Robots (RUR), but the Jewish legend of the golem that it clearly drew inspiration from. In that tale, artificial life exists to defend people against violent oppression. Although the original fable sees the golem run amok, the idea of the creature endures as an empowering fantasy in a time of rising anti-Semitism. The myth has left its mark on everything from superhero fantasies to tales of benevolent robots—narratives where artificial or alien life is in communion with human life and arrayed against the ugliest forces that sapience can produce. If that isn’t relevant, nothing is.

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Governments around the world are rushing to embrace the algorithms that breathed some semblance of intelligence into ChatGPT, apparently enthralled by the enormous economic payoff expected from the technology. Two new reports out this week show that nation-states are also likely rushing to adapt the same technology into weapons of misinformation, in what could become a troubling AI arms race between great powers. Researchers at RAND, a nonprofit think tank that advises the United States government, point to evidence of a Chinese military researcher who has experience with information campaigns publicly discussing how generative AI could help such work. One research article, from January 2023, suggests using large language models such as a fine-tuned version of Google’s BERT, a precursor to the more powerful and capable language models that power chatbots like ChatGPT. “There’s no evidence of it being done right now,” says William Marcellino, an AI expert and senior behavioral and social scientist at RAND, who contributed to the report. “Rather someone saying, ‘Here’s a path forward.’” He and others at RAND are alarmed at the prospect of influence campaigns getting new scale and power thanks to generative AI. “Coming up with a system to create millions of fake accounts that purport to be Taiwanese, or Americans, or Germans, that are pushing a state narrative—I think that it’s qualitatively and quantitatively different,” Marcellino says. Online information campaigns, like the one that Russia’s Internet Research Agency waged to undermine the 2016 US election, have been around for years. They have mostly depended on manual labor—human workers toiling at keyboards. But AI algorithms developed in recent years could potentially mass-produce text, imagery, and video designed to deceive or persuade, or even carry out convincing interactions with people on social media platforms. A recent project suggests that launching such a campaign could cost just a few hundred dollars. Marcellino and his coauthors note that many countries—the US included— are almost certainly exploring the use of generative AI for their own information campaigns. And the wide accessibility of generative AI tools, including numerous open source language models anyone can obtain and modify, lowers the bar for anyone looking to launch an information campaign. “A variety of actors could use generative AI for social media manipulation, including technically sophisticated non-state actors,” they write. A second report issued this week, by another tech-focused think tank, the Special Competitive Studies Project, also warns that generative AI could soon become a way for nations to flex on one another. It urges the US government to invest heavily in generative AI because the technology promises to boost many different industries and provide “new military capabilities, economic prosperity, and cultural influence” for whichever nation masters it first. Like the RAND report, the SCSP’s analysis also draws some gloomy conclusions. It warns that generative AI’s potential is likely to trigger an arms race to adapt the technology for use by militaries or in cyberattacks. If both are right, we are headed for an information-space arms race that may prove particularly difficult to contain. How to avoid the nightmare scenario of the internet becoming overrun with AI bots programmed for information warfare? It requires humans to talk with one another. The SCSP report recommends that the US “should lead global engagement to promote transparency, foster trust, and encourage collaboration.” The RAND researchers recommend that US and Chinese diplomats discuss generative AI and the risks around the technology. “It may be in all of our interests not to have an internet that’s totally polluted and unbelievable,” Marcellino says. I think that’s something we can all agree on.

The Ministry of Finance notified amendments to the Central GST law for calculating the value of supply by online gaming platforms The order also stated that winnings by any player will remain tax-neutral as the entire tax is collected at the first stage itself The development comes a month after the Parliament approved amendments to the Central and Integrated GST laws to levy a 28% tax on the full face value of bets for online gaming Putting its rubber stamp on the 28% GST regime, the union government on Friday (September 1) notified amendments specifying valuation methodology to be used by online gaming platforms for calculating tax liability.  Following the GST Council’s recommendations, the Ministry of Finance notified amendments to the Central GST law for calculating the value of supply by online gaming platforms. Further clearing the air, the order stated that winnings by any player will remain tax-neutral as the entire tax is collected at the first stage itself.  The development comes a month after the Parliament approved amendments to the Central and Integrated GST laws to levy a 28% tax on the full face value of bets for online gaming. Reacting to the development, EY Tax Partner Saurabh Agarwal told news agency PTI that the notification is expected to effectively settle the ambiguity and uncertainty around this matter. He, however, added, “… the aspect of whether the mere deposit of money in a wallet qualifies as a supply is unclear, and may be challenged by the industry.” This follows the GST Council’s decision to impose a 28% GST on the amount being paid at the entry level for online gaming in July this year. As the government moved ahead with its plans to solidify the levy, Indian online gaming platforms made a beeline, seeking revocation of the proposed plans.  Despite criticism from all quarters of the gaming industry, the Centre stuck with plans and passed the amendments in the Parliament. Since then, the gaming ecosystem has been gripped by crises.  Last month, Mobile Premier League (MPL) slashed half of its workforce to cut corners. This was followed by Hike and Spartan Poker firing employees in droves as they grappled with the tax burden.  On top of that, Inc42 recently reported that more than 20-25% of online gaming platforms are mulling to get acquired or acquihired. An analyst even said that these startups were selling for pennies on a dollar.  As the crisis mounts, it remains to be seen how the industry reacts to the new curveball.

AI-generated content is almost everywhere now. Companies like Google, Microsoft among others have AI tools that can generate text, images, video, audio, and much more. Keeping in mind, the potential misuse of AI-generated content, Google has made changes to its political content policy. Starting in November, Google will require election advertisers to put a disclaimer. “All verified election advertisers in regions where verification is required must prominently disclose when their ads contain synthetic content that inauthentically depicts real or realistic-looking people or events,” said Google in a post on its support page. In other words, if a video has any form of content that has been generated using AI, then it should come with a disclaimer. “This disclosure must be clear and conspicuous, and must be placed in a location where it is likely to be noticed by users,” said Google. The rule will apply to image, video, and audio content.Google also gives examples of what can be classified as “synthetic” content. An ad with synthetic content that makes it appear as if a person is saying or doing something they didn’t say or do. Or an ad with synthetic content that alters footage of a real event or generates a realistic portrayal of an event to depict scenes that did not actually take place. What ads won’t need a disclaimer?Google also said that “ads that contain synthetic content altered or generated in such a way that is inconsequential to the claims made in the ad will be exempt from these disclosure requirements. “This includes editing techniques such as image resizing, cropping, color or brightening corrections, defect correction (for example, “red eye” removal), or background edits that do not create realistic depictions of actual events,” said Google.In the US, a few political campaigns have seen the rise of AI content in videos.

An award-winning piece of AI art cannot be copyrighted, the US Copyright Office has ruled. The artwork, Théâtre D’opéra Spatial, was created by Matthew Allen and came first in last year’s Colorado State Fair. Since then, the piece has been embroiled in a precedent-affirming copyright dispute. Now, the government agency has issued its third and final decision: Allen’s work is not eligible for copyright. Now, Allen plans to file a lawsuit against the US federal government. “I’m going to fight this like hell,” he says. The problem? Allen used the generative AI program Midjourney to create his entry, and copyright protections are not extended to artificial intelligence—not even the kind that wows art judges. “It’s in line with previous decisions that require human authors,” says Rebecca Tushnet, a Harvard Law School professor and leading copyright scholar. It’s a precedent that goes back to 2018 when a photo taken by a macaque was declared public domain because monkeys can’t hold copyright. PETA may beg to differ, but under the law, monkeys and machines have about the same claim on copyright protections right now. (And this isn’t just in the US. In nearly every country, copyright is pegged to human authorship.) Allen was dogged in his attempt to register his work. He sent a written explanation to the Copyright Office detailing how much he’d done to manipulate what Midjourney conjured, as well as how much he fiddled with the raw image, using Adobe Photoshop to fix flaws and Gigapixel AI to increase the size and resolution. He specified that creating the painting had required at least 624 text prompts and input revisions. The Copyright Office agreed that the parts of the painting that Allen had altered with Adobe constituted original work. However, it maintained that other parts generated by AI could not be copyrighted. In other words: Allen could copyright parts of the painting, but not the whole thing. This July, Allen appealed once more, arguing that the office had ignored “the essential element of human creativity” needed to use Midjourney. He attempted to use the fair use doctrine to argue that his work should be registered, because it amounts to a transformative use of copyrighted material. “The underlying AI generated work merely constitutes raw material which Mr. Allen has transformed through his artistic contributions,” Allen wrote. The Copyright Office didn’t buy it. “The work cannot be registered,” it wrote in its final ruling on September 5. Allen’s dashed efforts highlight a solidifying legal consensus. This August, a US federal judge dismissed a case brought by Missouri-based AI researcher Stephen Thalus, who has been on a mission to prove that the AI system he invented deserves copyright protections. “Plaintiff can point to no case in which a court has recognized copyright in a work originating with a nonhuman,” wrote Judge Beryl Howell of the US District Court for the District of Columbia in her decision. Thalus is currently appealing the verdict. Ryan Abbot, his attorney, does not believe that the Copyright Office’s decision on Allen will have an impact on his client’s appeal. But he does see it as having a chilling effect on the wider world of AI-assisted art. “I think it will be a major disincentive to people developing and using AI to make art,” Abbot says.

Modern-day cars are getting smarter by the day. However, it seems like there’s a huge privacy cost attached to it, claims a research report by Mozilla. “While we worried that our doorbells and watches that connect to the internet might be spying on us, car brands quietly entered the data business by turning their vehicles into powerful data-gobbling machines,” says Mozilla in a blog post. Mozilla reviewed 25 car brands in its research (in the US) to find out how those companies collect and use your data and personal information. The result? “Every car brand we looked at collects more personal data than necessary and uses that information for a reason other than to operate your vehicle and manage their relationship with you,” says Mozilla. Your data is being sold While collecting data is something almost every company ends up doing, car companies, as per Mozilla are selling that data as well. Almost 84% of the car brands Mozilla researches said they can share your data with other businesses, service providers and data brokers. 19% said that they can also sell your data.Bizarrely, the likes of Kia and Nissan say that they can collect information related to users’ sex life. The privacy policies of both car companies, as per Mozilla’s research, information about your sexual activity and sex life. Of all the privacy tests, Mozilla conducted Elon Musk-owned Tesla failed on all counts. A key reason behind this is Tesla’s AI-powered autopilot feature, which has led to several deaths and remains under investigation as well. Mozilla claims that it spent over 600 hours researching the car brands’ privacy practices, which is almost three times on any other product. “Even still, we were left with so many questions. None of the privacy policies promises a full picture of how your data is used and shared,” said Mozilla.