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Archivo del Autor: Belen De Leon

How and why to make homemade dog food – CNET

For those who want to feed Fido only the very finest chow.
Source: CNET

Time spent on smartphones isn’t damaging teens’ mental health, study shows

A new study investigated how much time young people spend using technology and its effects on their mental health. and spoiler alert: The researchers didn’t find a link between technology use and mental health.
Source: Digital trends

Web host Hostinger says data breach may affect 14 million customers

Hostinger said it has reset user passwords as a “precautionary measure” after it detected unauthorized access to a database containing information on millions of its customers.

The breach is said to have happened on Thursday. The company said in a blog post it received an alert that one of its servers was improperly accessed. Using an access token found on the server, which can give access to systems without needing a username or a password, the hacker gained further access to the company’s systems, including an API database. That database contained customer usernames, email addresses, and passwords scrambled with the SHA-1 algorithm, which has been deprecated in favor of stronger algorithms after researchers found SHA-1 was vulnerable to spoofing. The company has since upgraded its password hashing to the stronger SHA-2 algorithm.

Hostinger said the API database stored about 14 million customers records. The company has more than 29 million customers on its books.

The company said it was “in contact with the respective authorities.”

hostinger

An email from Hostinger explaining the data breach. (Image: supplied)

News of the breach broke overnight. According to the company’s status page, affected customers have already received an email to reset their passwords.

The company said that financial data was not compromised, nor was customer website files or data affected.

But one customer who was affected by the breach accused the company of being potentially “misleading” about the scope of the breach.

A chat log seen by TechCrunch shows a customer support representative telling the customer it was “correct” that customers’ financial data can be retrieved by the API but that the company does “not store any payment data.” Hostinger uses multiple payment processors, the representative told the customer, but did not name them.

Chief executive Balys Kriksciunas told TechCrunch that the remarks made by the customer support representative were “misleading” and denied any customer financial data was compromised. A company investigation into the breach, however, remains under way.

Updated with remarks from Hostinger.

Related stories:


Source: TechCrunch

Original Content podcast: Netflix’s ‘Red Sea Diving Resort’ awkwardly mixes fiction and reality

“The Red Sea Diving Resort,” a new film on Netflix, is based on the true story of Mossad agents who took over an abandoned holiday resort in Sudan to smuggle Jewish Ethiopian refugees out of the country.

As we explain in the latest episode of the Original Content podcast, the film feels like it’s made in the “Argo” mold, fashioning a political thriller out of a too-crazy-for-fiction events. But it’s not as well-made as “Argo,” while struggling with the same challenges — mixing serious and comedic tones, and balancing real-world politics with blockbuster thrills.

The balance feels particularly awkward with “Captain America” actor Chris Evans playing the Mossad agent leading the operation. He’s not bad in the role, but there’s not much substance or complexity to it, and his presence underlines the feeling that we’re watching a Hollywood fantasy.

The film also skimps on providing any broader political context. Maybe it deserves credit for not holding the audience’s hand, but as a result, all we know who the good guys are and who the bad guys. Meanwhile, none of the refugees — not even Kabede, who’s played by Michael K. Williams of “The Wire” — fully emerges a three-dimensional character.

Before our review, we discuss the apparent end of Disney and Sony’s agreement making Spider-Man part of the Marvel Cinematic Universe, news that prompted outrage and petitions from unhappy fans.

You can listen in the player below, subscribe using Apple Podcasts or find us in your podcast player of choice. If you like the show, please let us know by leaving a review on Apple. You can also send us feedback directly. (Or suggest shows and movies for us to review!)

And if you’d like to skip ahead, here’s how the episode breaks down:

0:00 Intro
2:25 Spider-Man news
14:37 “Red Sea Diving Resort” review
37:02 “Red Sea Diving Resort” spoiler discussion


Source: TechCrunch

The *Jeopardy!* Master is Making a Better Trivia Game

Ken Jennings is teaming up with the creator of *Magic* to launch *Half-Truth*, a game that will “make you feel smart when you play.”
Source: Wired

The risks of amoral A.I.

Artificial intelligence is now being used to make decisions about lives, livelihoods, and interactions in the real world in ways that pose real risks to people.

We were all skeptics once. Not that long ago, conventional wisdom held that machine intelligence showed great promise, but it was always just a few years away. Today there is absolute faith that the future has arrived.

It’s not that surprising with cars that (sometimes and under certain conditions) drive themselves and software that beats humans at games like chess and Go. You can’t blame people for being impressed.

But board games, even complicated ones, are a far cry from the messiness and uncertainty of real-life, and autonomous cars still aren’t actually sharing the road with us (at least not without some catastrophic failures).

AI is being used in a surprising number of applications, making judgments about job performance, hiring, loans, and criminal justice among many others. Most people are not aware of the potential risks in these judgments. They should be. There is a general feeling that technology is inherently neutral — even among many of those developing AI solutions. But AI developers make decisions and choose tradeoffs that affect outcomes. Developers are embedding ethical choices within the technology but without thinking about their decisions in those terms.

These tradeoffs are usually technical and subtle, and the downstream implications are not always obvious at the point the decisions are made.

The fatal Uber accident in Tempe, Arizona, is a (not-subtle) but good illustrative example that makes it easy to see how it happens.

The autonomous vehicle system actually detected the pedestrian in time to stop but the developers had tweaked the emergency braking system in favor of not braking too much, balancing a tradeoff between jerky driving and safety. The Uber developers opted for the more commercially viable choice. Eventually autonomous driving technology will improve to a point that allows for both safety and smooth driving, but will we put autonomous cars on the road before that happens? Pro�t interests are pushing hard to get them on the road immediately.

Physical risks pose an obvious danger, but there has been real harm from automated decision-making systems as well. AI does, in fact, have the potential to bene�t the world. Ideally, we mitigate for the downsides in order to get the bene�ts with minimal harm.

A signi�cant risk is that we advance the use of AI technology at the cost of reducing individual human rights. We’re already seeing that happen. One important example is that the right to appeal judicial decisions is weakened when AI tools are involved. In many other cases, individuals don’t even know that a choice not to hire, promote, or extend a loan to them was informed by a statistical algorithm. 

Buyer Beware

Buyers of the technology are at a disadvantage when they know so much less about it than the sellers do. For the most part decision makers are not equipped to evaluate intelligent systems. In economic terms, there is an information asymmetry that puts AI developers in a more powerful position over those who might use it. (Side note: the subjects of AI decisions generally have no power at all.) The nature of AI is that you simply trust (or not) the decisions it makes. You can’t ask technology why it decided something or if it considered other alternatives or suggest hypotheticals to explore variations on the question you asked. Given the current trust in technology, vendors’ promises about a cheaper and faster way to get the job done can be very enticing.

So far, we as a society have not had a way to assess the value of algorithms against the costs they impose on society. There has been very little public discussion even when government entities decide to adopt new AI solutions. Worse than that, information about the data used for training the system plus its weighting schemes, model selection, and other choices vendors make while developing the software are deemed trade secrets and therefore not available for discussion.

Image via Getty Images / sorbetto

The Yale Journal of Law and Technology published a paper by Robert Brauneis and Ellen P. Goodman where they describe their efforts to test the transparency around government adoption of data analytics tools for predictive algorithms. They �led forty-two open records requests to various public agencies about their use of decision-making support tools.

Their “speci�c goal was to assess whether open records processes would enable citizens to discover what policy judgments these algorithms embody and to evaluate their utility and fairness�. Nearly all of the agencies involved were either unwilling or unable to provide information that could lead to an understanding of how the algorithms worked to decide citizens’ fates. Government record-keeping was one of the biggest problems, but companies’ aggressive trade secret and con�dentiality claims were also a signi�cant factor.

Using data-driven risk assessment tools can be useful especially in cases identifying low-risk individuals who can bene�t from reduced prison sentences. Reduced or waived sentences alleviate stresses on the prison system and bene�t the individuals, their families, and communities as well. Despite the possible upsides, if these tools interfere with Constitutional rights to due process, they are not worth the risk.

All of us have the right to question the accuracy and relevance of information used in judicial proceedings and in many other situations as well. Unfortunately for the citizens of Wisconsin, the argument that a company’s pro�t interest outweighs a defendant’s right to due process was affirmed by that state’s supreme court in 2016.

Fairness is in the Eye of the Beholder

Of course, human judgment is biased too. Indeed, professional cultures have had to evolve to address it. Judges for example, strive to separate their prejudices from their judgments, and there are processes to challenge the fairness of judicial decisions.

In the United States, the 1968 Fair Housing Act was passed to ensure that real-estate professionals conduct their business without discriminating against clients. Technology companies do not have such a culture. Recent news has shown just the opposite. For individual AI developers, the focus is on getting the algorithms correct with high accuracy for whatever de�nition of accuracy they assume in their modeling.

I recently listened to a podcast where the conversation wondered whether talk about bias in AI wasn’t holding machines to a different standard than humans—seeming to suggest that machines were being put at a disadvantage in some imagined competition with humans.

As true technology believers, the host and guest eventually concluded that once AI researchers have solved the machine bias problem, we’ll have a new, even better standard for humans to live up to, and at that point the machines can teach humans how to avoid bias. The implication is that there is an objective answer out there, and while we humans have struggled to �nd it, the machines can show us the way. The truth is that in many cases there are contradictory notions about what it means to be fair.

A handful of research papers have come out in the past couple of years that tackle the question of fairness from a statistical and mathematical point-of-view. One of the papers, for example, formalizes some basic criteria to determine if a decision is fair.

In their formalization, in most situations, differing ideas about what it means to be fair are not just different but actually incompatible. A single objective solution that can be called fair simply doesn’t exist, making it impossible for statistically trained machines to answer these questions. Considered in this light, a conversation about machines giving human beings lessons in fairness sounds more like theater of the absurd than a purported thoughtful conversation about the issues involved.

Image courtesy of TechCrunch/Bryce Durbin

When there are questions of bias, a discussion is necessary. What it means to be fair in contexts like criminal sentencing, granting loans, job and college opportunities, for example, have not been settled and unfortunately contain political elements. We’re being asked to join in an illusion that arti�cial intelligence can somehow de-politicize these issues. The fact is, the technology embodies a particular stance, but we don’t know what it is.

Technologists with their heads down focused on algorithms are determining important structural issues and making policy choices. This removes the collective conversation and cuts off input from other points-of-view. Sociologists, historians, political scientists, and above all stakeholders within the community would have a lot to contribute to the debate. Applying AI for these tricky problems paints a veneer of science that tries to dole out apolitical solutions to difficult questions. 

Who Will Watch the (AI) Watchers?

One major driver of the current trend to adopt AI solutions is that the negative externalities from the use of AI are not borne by the companies developing it. Typically, we address this situation with government regulation. Industrial pollution, for example, is restricted because it creates a future cost to society. We also use regulation to protect individuals in situations where they may come to harm.

Both of these potential negative consequences exist in our current uses of AI. For self-driving cars, there are already regulatory bodies involved, so we can expect a public dialog about when and in what ways AI driven vehicles can be used. What about the other uses of AI? Currently, except for some action by New York City, there is exactly zero regulation around the use of AI. The most basic assurances of algorithmic accountability are not guaranteed for either users of technology or the subjects of automated decision making.

GettyImages 823303786

Image via Getty Images / nadia_bormotova

Unfortunately, we can’t leave it to companies to police themselves. Facebook’s slogan, “Move fast and break things� has been retired, but the mindset and the culture persist throughout Silicon Valley. An attitude of doing what you think is best and apologizing later continues to dominate.

This has apparently been effective when building systems to upsell consumers or connect riders with drivers. It becomes completely unacceptable when you make decisions affecting people’s lives. Even if well-intentioned, the researchers and developers writing the code don’t have the training or, at the risk of offending some wonderful colleagues, the inclination to think about these issues.

I’ve seen �rsthand too many researchers who demonstrate a surprising nonchalance about the human impact. I recently attended an innovation conference just outside of Silicon Valley. One of the presentations included a doctored video of a very famous person delivering a speech that never actually took place. The manipulation of the video was completely imperceptible.

When the researcher was asked about the implications of deceptive technology, she was dismissive of the question. Her answer was essentially, “I make the technology and then leave those questions to the social scientists to work out.� This is just one of the worst examples I’ve seen from many researchers who don’t have these issues on their radars. I suppose that requiring computer scientists to double major in moral philosophy isn’t practical, but the lack of concern is striking.

Recently we learned that Amazon abandoned an in-house technology that they had been testing to select the best resumes from among their applicants. Amazon discovered that the system they created developed a preference for male candidates, in effect, penalizing women who applied. In this case, Amazon was sufficiently motivated to ensure their own technology was working as effectively as possible, but will other companies be as vigilant?

As a matter of fact, Reuters reports that other companies are blithely moving ahead with AI for hiring. A third-party vendor selling such technology actually has no incentive to test that it’s not biased unless customers demand it, and as I mentioned, decision makers are mostly not in a position to have that conversation. Again, human bias plays a part in hiring too. But companies can and should deal with that.

With machine learning, they can’t be sure what discriminatory features the system might learn. Absent the market forces, unless companies are compelled to be transparent about the development and their use of opaque technology in domains where fairness matters, it’s not going to happen.

Accountability and transparency are paramount to safely using AI in real-world applications. Regulations could require access to basic information about the technology. Since no solution is completely accurate, the regulation should allow adopters to understand the effects of errors. Are errors relatively minor or major? Uber’s use of AI killed a pedestrian. How bad is the worst-case scenario in other applications? How are algorithms trained? What data was used for training and how was it assessed to determine its �tness for the intended purpose? Does it truly represent the people under consideration? Does it contain biases? Only by having access to this kind of information can stakeholders make informed decisions about appropriate risks and tradeoffs.

At this point, we might have to face the fact that our current uses of AI are getting ahead of its capabilities and that using it safely requires a lot more thought than it’s getting now.


Source: TechCrunch

Lenovo ThinkBook 13s review

The Lenovo ThinkBook 13s tries – but mostly fails — to provide small and medium business users with enough business features to woo them away from competing consumer offerings.
Source: Digital trends

Crypto means cryptotheology

Cryptocurrencies are a religion as much as they are a technology. They almost have to be, given their adherents’ gargantuan ambition of fundamentally changing how the world works. This means they attract charlatans, lunatics, frauds, and false prophets, and furious battles are waged over doctrinal hairspliitting; but it also means they inspire intransigent beliefs which can, and do, unify many thousands of wildly different people across continents and time zones.

This occurred to me while I was rereading Gibbon’s Decline and Fall, as one does, and in particular its depictions of the early days of the Christian faith:

But whatever difference of opinion might subsist between the Orthodox [church], the Ebionites, and the Gnostics, concerning the divinity or the obligation of the Mosaic law, they were all equally animated by the same exclusive zeal; and by the same abhorrence for idolatry ..,. the established religions of Paganism were seen by the primitive Christians in a much more odious and formidable light. It was the universal sentiment both of the church and of heretics, that the daemons were the authors, the patrons, and the objects of idolatry.

For Orthodox church, Ebionites, and Gnostics, you can read perhaps, “Bitcoin maximalists”, “Blockchain not bitcoin,” and “Ethereum maximalists.” They disagree bitterly, but one view they all share is a disdain verging and frequently exceeding contempt for fiat currencies, untokenized assets, and most other aspects of money and finance as they are currently constructed. Instead they share a deep belief in the superiority, and inevitable supremacy, very different world.

The superstitious observances of public or private rites were carelessly practised, from education and habit, by the followers of the established religion. But as often as they occurred, they afforded the Christians an opportunity of declaring and confirming their zealous opposition. By these frequent protestations their attachment to the faith was continually fortified; and in proportion to the increase of zeal, they combated with the more ardor and success in the holy war, which they had undertaken against the empire of the demons.

I think few will disagree that, similarly, many cryptocurrency devotees seek out and seize every “opportunity of declaring and confirming their zealous opposition” to government money, central banks, rival maximalists, and other features of the monetary, financial, and/or centralized status quo.

The careless Polytheist, assailed by new and unexpected terrors, against which neither his priests nor his philosophers could afford him any certain protection, was very frequently terrified and subdued by the menace of eternal tortures. His fears might assist the progress of his faith and reason; and if he could once persuade himself to suspect that the Christian religion might possibly be true, it became an easy task to convince him that it was the safest and most prudent party that he could possibly embrace.

Similarly I don’t think it’s controversial to note that prophecies of the hyperinflation and collapse of national currencies, the downfall of central banks and fractional reserve banking in general, etc., are not unheard of among some of the … edgier … cryptocurrency people. One might even refer to the notion of “preaching the gospel” of deflationary, censorship-resistant cryptocurrency, sometimes in the hopes of scaring everyone who hears this doomsaying into buying some Bitcoin as a hedge.

Of course the religious parallels do not end with Gibbon. Cryptocurrencies were given to us not by a known, living, breathing, flawed human being, but by a pseudonymous verging-on-mythical quasi-demigod. (Cf eg “Satoshi’s Vision.”) Mythically speaking, that’s easily analogized to Prometheus granting humanity fire, or Moses bringing the stone tablets down from Mount Sinai. They have real and false prophets. There’s even a “Bitcoin Jesus.” And all promise a better world tomorrow, while demanding sacrifices and inconveniences today.

My tongue is obviously in cheek here — but I’m not entirely unserious. Of course all money is ultimately backed by faith (cf “full faith and credit.”) But this is I think unquestionably more true of cryptocurrencies, especially because, a decade on from their creation, they have failed — so far! — to transform the world to a degree anything like their proclaimed potential.

Bitcoin itself is apparently going from strength to strength, as can be seen in its increasing dominance of total cryptocurrency market capitalization, but it’s still beyond tiny compared to the rest of the financial world. Its total trading volume as I write this is roughly ~$15 billion per day, which admittedly sounds like a lot, but compared to the $5.1 trillion a day for the forex market as a whole, it’s roughly one-quarter of one percent.

More importantly, Bitcoin continues to technically iterate (although I’ve grown skeptical about Lightning, which it seems to me will always suffer from all the end-user inconveniences of prepaid credit cards, with few balancing advantages) and has hovered near or above $10,000 in value for months now. But the uncertainties and investigations regarding Tether remain a threatening cloud on its horizon.

As for other cryptocurrencies, though — well, these are complex times.

Ethereum, the best-known and perhaps most interesting, has gone from a wave of DAO excitement shortly after its launch, which faltered, to a wave of ICO madness and “fat protocol” DApps (decentralized applications), which also faltered, to the latest wave and watchword, “DeFi” aka decentralized finance. This essentially aims to reinvent all of Wall Street and the City of London on the blockchain(s), in the long term.

Meanwhile, the technical underpinnings that would allow Ethereum to scale to Wall Street size, known as “Ethereum 2.0,” remain more notional than real. I’m a big fan of Ethereum (my own pet crypto project is built on it) and I don’t think DeFi is doomed to failure … but under the circumstances I can understand skepticism creeping in among those who are not true believers.

There are plenty of other technically interesting cryptocurrency initiatives: from privacy coins such as ZCash, Monero, and Grin, to the use of Tezos by Brazil’s fifth largest bank for security tokens (again, DeFi), to the growth and stabilization of Cosmos’s “internet of blockchains,” to Blockstack’s total-app-installs graph beginning to look a little more exponential than linear, albeit with still-tiny y-axis numbers.

However, I think it’s also fair to say that now that cryptocurrencies are no longer new, unknown, and fascinating, interest among both individuals and enterprises who are not true believers has waned considerably. The cultural whiplash one experiences when transitioning from a conference full of people convinced they are building a new technology that will transform the fundamental order of the world, to outsiders (even technical outsiders) remarking “oh, is that still a thing?” is increasingly sharp.

That was probably true of the Christians after they ceased to be new and interesting, though, and in the end the Christians conquered the most powerful empire in the world from within. I am definitely not prophesying the same outcome here. I continue to think cryptocurrencies will remain a financial alternative, albeit a very significant and important one, used only by a few percent of people.

But I am saying that seeming increasingly distant from the external consensus reality, being driven by intransigent and sometimes bewildering faith as much as rational analysis, and ongoing associations with a cloud of crazy scandal and hangers-on snake-oil salespeople — all of which would be catastrophic signs for, say, a traditional new startup — can actually be indicators of the strength, not weakness, of a strange new religion. Something to bear in mind as we move into the second decade of cryptocurrencies.


Source: TechCrunch

Bugatti's Centodieci, VW's Electric Dune Buggy, and More Cars News

Plus, an inside look at Netflix’s crazy new car show and Ford’s plan to gather data from college scooter riders.
Source: Wired

While You Were Offline: Who Wants to See Sean Spicer’s Samba?

Not us, and not Tom Bergeron!
Source: Wired

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