Director of National Intelligence Releases Six Principles for Ethical AI

US intelligence agencies have released six principles for the ethical use of AI, emphasizing transparency, equity and security. (GETTY IMAGES)

By AI Trends Staff

This week, the Office of the Director of National Intelligence (ODNI) released the first of an evolving set of principles for the ethical use of AI. The six principles, ranging from privacy to transparency to cybersecurity, were described as Version 1.0 and were approved by John Ratcliffe, Director of National Intelligence.

The six principles are positioned as a guide for the nation’s 17 intelligence agencies, especially to help them work with private companies contracted to help the government build systems incorporating AI, according to an account in Breaking Defense. The intelligence agency principles complement the AI principles adopted by the Pentagon earlier this year.

“These AI ethics principles don’t diminish our ability to achieve our national security mission,” stated Ben Huebner, head of the Office of Civil Liberties, Privacy, and Transparency at ODNI. “To the contrary, they help us ensure that our AI or use of AI provides unbiased, objective and actionable intelligence policymakers require that is fundamentally our mission.”

Ben Huebner, head of the Office of Civil Liberties, Privacy, and Transparency, ODNI

Feedback on the intelligence community’s AI principle is welcome, its managers say. “We are absolutely welcoming public comment and feedback on this,” stated Huebner, noting that there will be a way for public feedback at Intel.gov. “No question at all that there are aspects of what we do that are and remain classified. I think though, what we can do is talk in general terms about some things that we are doing.”

Dean Souleles, Chief Technology Advisor for ODNI, said the “science of AI is not 100% complete yet,” but the ethics documents give intelligence officials a current roadmap of how best to use this emerging technology.

“It is too early to define a long list of do’s and don’ts. We need to understand how this technology works, we need to spend our time under the framework and guidelines that we’re putting out to make sure that we’re staying within the guidelines. But this is a very, very fast-moving train with this technology,” stated Souleles, in an account in Federal News Network.

Feedback is Welcome

The intelligence community expects to release updates to its AI documents as the technology evolves and it responds to questions. One of the issues being considered by the intelligence agencies is – what is the role of the “human-in-the-loop,” in the parlance of the DoD. For example, if a voice-to-text application has been trained in a dialect from one region of the world, even if it is the same language, how accurate it is? “That’s something I need to know about,” stated Huebner.

Feedback to the intelligence agencies on their AI principles is likely to derive from examples in the private sector. “We think there’s a big overlap between what the intelligence community needs and frankly, what the private sector needs that we can and should be working on, collectively together,” stated Souleles.

Dean Souleles, Chief Technology Advisor, ODNI

For example, in trying to identify the source of a threat, examples from business could be helpful to the intelligence community, which is both reassuring and ominous.

“There are many areas we’re going to be able to talk about going forward, where there’s overlap that does not expose our classified sources and methods,” stated Souleles, “because many, many, many of these things are really common problems.”

A major concern with AI, no matter who is developing it, is bias in algorithms, according to an account in C4Isrnet. The framework suggests steps for practitioners to take to discover undesired biases that may enter algorithms throughout the life cycle of an AI program.

“The important thing for intelligence analysts is to understand the sources of the data that we have, the inherent biases in those data, and then to be able to make their conclusions based on the understanding of that,” Souleles stated. “And that is not substantially different from the core mission of intelligence. We always deal with uncertainty.”

Here are the six principles, in the document’s own words:

Respect the Law and Act with Integrity. We will employ AI in a manner that respects human dignity, rights, and freedoms. Our use of AI will fully comply with applicable legal authorities and with policies and procedures that protect privacy, civil rights, and civil liberties.

Transparent and Accountable. We will provide appropriate transparency to the public and our customers regarding our AI methods, applications, and uses within the bounds of security, technology, and releasability by law and policy, and consistent with the Principles of Intelligence Transparency for the IC. We will develop and employ mechanisms to identify responsibilities and provide accountability for the use of AI and its outcomes.

Objective and Equitable. Consistent with our commitment to providing objective intelligence, we will take affirmative steps to identify and mitigate bias.

Human-Centered Development and Use. We will develop and use AI to augment our national security and enhance our trusted partnerships by tempering technological guidance with the application of human judgment, especially when an action has the potential to deprive individuals of constitutional rights or interfere with their free exercise of civil liberties.

Secure and Resilient. We will develop and employ best practices for maximizing reliability, security, and accuracy of AI design, development, and use. We will employ security best practices to build resilience and minimize potential for adversarial influence.

Informed by Science and Technology. We will apply rigor in our development and use of AI by actively engaging both across the IC and with the broader scientific and technology communities to utilize advances in research and best practices from the public and private sector.

Read the source articles in Breaking Defense, Federal News Network and C4Isrnet. Read the intelligence community’s AI principles at Intel.gov.

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Apple acquires startup that turns iPhones into payment terminals, reportedly for $100 million – 9to5Mac

Apple has acquired a startup, Mobeewave Inc., that developed technology to turn iPhones into mobile payment terminals, according to a new report from Bloomberg. Citing people familiar with the matter, today’s report says the deal was worth around $100 million.

Apple confirmed the deal with its standard statement about its acquisition strategy. “Apple buys smaller technology companies from time to time and we generally do not discuss our purpose or plans,” an Apple spokesman told Bloomberg. The company did not confirm the reported $100 million acquisition price.

Mobeewave bills its technology as a way to seamlessly accept credit card payments “with a tap on your phone.” What this means is that a shopper could simply tap their credit card or smartphone on the back of smartphone to process a payment. The system works via an app from Mobeewave as well as NFC technology.

The demonstration on the Moobeewave website shows the process in three steps:

• Step one: Input the transaction amount
• Step two: Tap the client’s card onto the back of your device
• Step three: Payment is processed on your device

There are a variety of ways Apple could incorporate this technology into the iPhone or other products. This feature could be a way for Apple to expand its Apple Play platform and compete with Square’s point of sale platform. Furthermore, Apple Card debuted last year, and Mobeewave’s technology could integrate into that ecosystem, including the Apple Wallet app.

The news of the Mobeewave acquisition comes on the same as Apple CEO Tim Cook talked about Apple’s strategy for acquiring other companies. In an effort to differentiate Apple from other tech companies that might focus on acquiring potential competitors, Cook emphasized that Apple acquires a company to eventually implement its technology into the iPhone.

One of Apple’s most recent acquisitions was Dark Sky, a weather app that now serves as the basis of new features in the Weather app on iPhone in iOS 14. As 9to5Mac first reported, Apple this year also acquired NextVR, a virtual reality company focused on providing VR experiences for viewing live events.

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Apple shares close at new all-time high [Updated]

Apple is now valued at $1.78 trillion.
Photo: Ed Hardy/Cult of Mac

Apple shares hit a new all-time high Friday on the back of the company’s shockingly good Q3 earnings. AAPL closed up 10.47% at $425.04, fueled by Thursday’s record-breaking report.

Friday’s surge gives Apple a market cap of an astonishing $1.84 trillion, within spitting distance of the once-unimaginable $2 trillion valuation. And it makes Apple the most valuable publicly traded company in the world.

Apple first crossed the $1 trillion milestone in 2018. It then dropped back to the $900 billion mark, before climbing from there. Its current high price comes at a time when financial markets are taking a turn for the worse, based on fears about a second wave of COVID-19.

By comparison, other tech stocks are doing well — but not Apple well. Amazon is valued at $1.597 trillion. Google parent company Alphabet is valued at $1 trillion after a dip following a disappointing quarter. Facebook is worth $721 billion. And Microsoft is at $1.53 trillion.

Apple said Thursday that it will do a 4-to-1 stock split. The last time Apple stock split was in 2014, when it split 7-to-1. At the time, Apple reached its technical highest valuation per share — with the cost of a single Apple share being $705. Had that stock split not taken place, those pre-split Apple shares would be worth more than $2,874.83.

Kind of makes you wish you’d invested in AAPL at the time, right? No wonder Warren Buffett’s Berkshire Hathaway company is so bullish on all things Apple.

Originally posted at 8:45 a.m. Pacific, this post was updated after the market closed Friday.

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Pocketnow Daily: Apple Confirms iPhone 12 Delays… (video)

Apple’s new Mac mini, the Razer Blade 15 and more devices are on sale today

Deals. Let’s start today off with the Razer Blade 15 which is currently $285 off, leaving the Intel Core i7, 16GB of RAM and 256GB of SSD variant for $1315. Samsung is still trying to get rid of some inventory ahead of Unpacked, meaning that Amazon still has the Galaxy Z Flip bundled with a free Galaxy Watch Active 2 for $1380 ship-ped. The S20 5G is getting the same treatment, leaving that at $999 with the free watch as well. The Mac Mini is currently $173 off, leaving the Intel Core i5, 8GB of RAM and 128GB of storage one for $927. We have more deals on TCL phones, Xbox and Razer controllers, Jabra Earbuds and more.

17-year old Florida teen arrested for being the mastermind behind Twitter’s massive hack

Do you remember a couple of weeks ago when Twitter was on fire? You know when someone hacked major celebrity accounts and ran a Bitcoin scam? Well, a 17 year old from Tampa, Florida was just arrested as the mastermind of the whole thing which was achieved by using a phone spear phishing attack. According to this very high quality video from the Executive Office for United States Attorney, who apparently can’t afford a better camera capable of doing 720p, this guy is facing 29 counts of fraud. They also took other people into custody from Orlando Florida and they apparently made $100K from over 400 separate transactions.

Nvidia is reportedly in advanced talks to buy semiconductor giant ARM

It looks like Nvidia is about to make a big purchase. According to a new report, Nvidia and Softbank are in advanced talks as Nvidia wants to purchase UK-based chip designer Arm. This would reportedly be a cash-and-stock deal that would value Arm at over $32B. A different Bloomberg report claims that both companies will be reaching a deal in the next few weeks. Nvidia is currently valued at $260B and purchasing Arm, who have chips in phones, PCs, TVs and more will only boost Nvidia’s influence over the market. We’ll keep you posted to see if the deal actually goes through.

Google Pixel 5a gets mentioned before the launch of the Pixel 4a

Pixel 4a may launch soon, but the Google Pixel 2 will lose support

Oh, you thought we waited and got too many leaks of the Pixel 4a? Relax, the Pixel 5a is here. The guys over at 9to5Google just uncovered the rest of Google’s line up for 2020 and even 2021 from the AOSP. The leak includes the Pixel 4a which we’ll hopefully be getting soon, the Pixel 4a 5G which we covered about a month ago and the Pixel 5. Now, where it gets it interesting is when the next phone is the Pixel 5a. We don’t really have any other information from it, other than the fact that it will most likely launch by the middle of next year even though, you never know with Google. Moving on from that, a different leak that also comes from the AOSP shows that Google will be dropping support for the Pixel 2 once they release Android 11. The leak also confirms that the Pixel 4a will launch with Android 10 as we usually get the official version of Android until September or October.

Apple’s annual iPhone shipments grow, as Huawei takes Samsung’s crown

A couple of days ago we discussed how Apple’s numbers grew significantly in China during Q2 and now we have some global numbers from Canalys and IDC that bring some surprises. Huawei overtook Samsung as the global leader with 55.8M shipments. What’s interesting is the fact that Huawei didn’t actually grow when compared to last year, they had a 5% decrease, the problem is that Samsung had a 30% decrease and they only achieved 53.7M shipments. In the third place we got Apple with 45.1M shipments and they actually grew 25% , when compared to Q2 in 2019 thanks to the iPhone 11 and the SE. The rest of the list is made up by Xiaomi, OPPO and others. According to Canalys analysts, the future of these companies is uncertain as Huawei is still going through multiple bans and of course, the fact that the pandemic is still going on.

Apple confirms the iPhone 12 series will be delayed by a few weeks

We know that Apple’s current timeline is messy but now we finally have some official news as to what to expect. Apple just announced their quarter results yesterday, posting a major $59.7B in revenue but they also made another major announcement. The company’s CFO stated that “last year they started selling iPhones in late September but this year, they project supply to be available until a few weeks later“. However, it isn’t clear if the whole line up has been delayed or just a few. And, this isn’t the first time Apple is doing something like this, we saw it with the iPhone X which was announced in September and hit shelves until November. We’ve also had multiple predictions and reports, like Ming Chi Kuo claiming we’d be getting the mmWave iPhones later. Earlier this week we also covered how there was a possible September 8th event but, we are expecting them to be available for purchase until October. Subscribe: http://bit.ly/pocketnowsub http://pocketnow.com Follow us: http://flipboard.com/@Pocketnow http://facebook.com/pocketnow http://twitter.com/pocketnow http://google.com/+pocketnow Source

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Trump told reporters he will use executive power to ban TikTok

President Donald Trump said he could act to ban the world’s most popular short video app TikTok from the US as early as Saturday, according to The Hill.

The president said he could use “emergency economic powers or an executive order” to bar TikTok from the US, he told reporters aboard Air Force One on Friday.

The news came hours after reports broke that Microsoft was in talks to buy TikTok. Investors are reportedly valuing three-year-old TikTok at $50 billion. In his remark on Friday, Trump signaled he was not supportive of allowing an American company to acquire TikTok.

On the same day, Bloomberg reported that Trump could order ByteDance to divest its ownership of TikTok.

In response to Trump’s decision, TikTok, as usual, tried to make a case that it’s in the interest of the US to keep the app and it poses no national security threat:

“100 million Americans come to TikTok for entertainment and connection, especially during the pandemic. We’ve hired nearly 1,000 people to our US team this year alone, and are proud to be hiring another 10,000 employees into great paying jobs across the US. Our $1 billion creator fund supports US creators who are building livelihoods from our platform. TikTok US user data is stored in the US, with strict controls on employee access. TikTok’s biggest investors come from the US. We are committed to protecting our users’ privacy and safety as we continue working to bring joy to families and meaningful careers to those who create on our platform,” said a TikTok spokesperson.

Trump’s announcement confirmed weeks of speculation that US regulators planned to block TikTok, which is immensely popular among American teens, over concerns that it could be a spying tool for Beijing.

The question is how a divestment or ban of TikTok will take shape. TikTok is owned by Beijing-based ByteDance, which has emerged as the most promising tech startup in China in recent times, reportedly valued at a staggering $100 billion. It operates Douyin, the popular Chinese version of TikTok, separately for China-based users.

ByteDance has sought various ways to distance TikTok from any Chinese association. Efforts in the past few months range from appointing former Disney executive Kevin Mayer as TikTok’s CEO, claiming the app’s data is stored on American land, through to promising to create 10,000 jobs in the US.

TikTok’s comms team also tried to assuage concerns by reiterating that four of its parent company’s five board seats are “controlled by some of the world’s best-respected global investors,” including Arthur Dantchik, managing director of Susquehanna International Group; William Ford, CEO of General Atlantic; Philippe Laffont, founder of Coatue Management; and Neil Shen, the boss of Sequoia China. ByteDance founder and CEO Zhang Yiming is the chairman of the board.

It’s worth noting that the Committee on Foreign Investment in the US (CFIUS) still hasn’t released its decision on whether the Musical.ly-TikTok merger constitutes a national security threat to the U.S. Even if it orders TikTok to shed Musical.ly, it’s unclear how the sale will happen in practice. When ByteDance merged the two apps back in 2018, it asked Musical.ly’s existing users to download the TikTok app, which already had users, so all of TikTok’s current users are, technically, TikTok users.

If the divestment is aimed at TikTok, will ByteDance be forced to sell all of its international assets? TikTok also has a substantial user base outside the US. Before India banned TikTok over national security fears, a favorite criticism among many US politicians, the country was the app’s largest overseas market.

It’s looking increasingly likely that Zhang Yiming’s worst nightmare is going to happen. The entrepreneur had aspirations to conquer the international market from the outset, and now his startup has become the latest pawn in US-China relations.

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First mention of Google “Pixel 5a” appears in AOSP

Google has finally confirmed that a Google Pixel 4a would be arriving on August 3 and even teased the device on Thursday. On Friday, 9to5Google’s own Dylan Roussel spotted a mention of Google’s Pixel 5a. This was spotted in a code change on Google’s Android Open Source Project or AOSP.

We are still waiting for the Google Pixel 5, which may not be released until later this year, but now we know that the 5a is now in development. The code change mentions devices since the Pixel 2, along with the version of Android they (launched/will launch) with.

The Pixel 4/4a are listed with “Q” for Android 10. However, a 5G-varaiant of the 4a will launch alongside the 5 later this year, both with the new Android R. But when will the Pixel 5a come out? We don’t know, but our guess is that Google might launch it halfway through the Pixel 5’s launch cycle like it did with the Pixel 3a.

Alleged leaked renders of Pixel 5 (left) and Pixel 5 XL (right)

We barely know what the Pixel 5 will actually look like, and its still too early to know what kind of hardware or features the Pixel 5a will have. Let’s wait for the Pixel 5 to arrive first, then we’ll talk.

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How one company is using machine learning to remove bias from the hiring process – WRAL Tech Wire

Editor’s note: Stuart Nisbet is chief data scientist at Cadient Talent, a talent acquisition firm based in Raleigh.

RALEIGH — At Cadient Talent, it’s a question that we wrestle with on a daily basis: How do we eliminate bias from the hiring process?

The only way to address a problem or bias is to acknowledge it head on, under the scrutiny of scientific examination. Through the application of machine learning, we are able to learn where we have erred in the past, allowing us to make less biased hiring decisions moving forward. When we uncover unconscious bias, or even conscious bias, and educate ourselves to do better based on unbiased machine learning we are able to take the first step toward correcting an identified problem.

What is bias?

Bias is defined as a prejudgment or a prejudice in favor of or against one thing, person, or group compared with another, usually in a way that is considered to be unfair. Think of bias as three sets of facts: The first is a set of objective facts that are universally accepted. The second is a set of facts that confirms beliefs, in line with what an individual believes to be true. Where bias enters the picture is in the intersection between the objective facts and the facts that confirm personal beliefs.

By selectively choosing the facts that confirm particular beliefs and focusing on the things that confirm those beliefs, bias enters. If we look at hiring from that perspective, and if our goal is to remove bias from the hiring process, then we need to remove the personal choice of which data points are included in the process. All data points that contribute to a positive choice (hire the applicant) or negative choice (decline the applicant) are included in the process and choosing the data points and their weights is done objectively through statistics, not subjectively through human choice.

How can computer algorithms help us do this? Our goal is to be able to augment the intelligence of humans, in particular by using the experiences and prior judgment in past hiring decisions, with an emphasis on those that resulted in good hiring decisions. “Good hiring” can be measured in a number of ways, that don’t implement inappropriate bias, such as the longevity of employees. If a new hire does not remain on the job very long, then perhaps the recruiting effort was not done well, and, in hindsight, you would not have chosen that applicant. But, if you hire someone who is productive and stays for a long time, that person would be considered a good hire.

Why do we want to remove bias from hiring decisions?

We want to remove bias when it is unintentional or has no bearing on whether an employee is going to be able to perform the job in a satisfactory manner. So, if a hiring manager’s entire responsibility is to apply their knowledge and experience to determine the best fit, why do we use machine learning to eliminate bias? Because, artificial intelligence only removes the bias towards non-work-related candidate attributes and augments decisions based on relevant work traits, where there is appropriate bias.

Our goal is then to make the hiring process as transparent as possible and consider all of the variables that are used in a hiring decision. That’s extremely complicated, if not impossible, if you have nothing but a human-based approach because the decision-making of a hiring manager is far more complex and less understood than those of a machine learning algorithm. So, we want to focus on the strength of simplicity in a machine learning algorithm; meaning we only want to look at variables, columns, and pieces of data in the algorithm that are pertinent to the hiring process and do not include any data points that are not relevant to performance.

Stuart Nisbet

An assessment result, for example, whether cognitive or personality-based, may be a very valid data point to consider if the traits being assessed are pertinent to the job. Work history and demonstrated achievement in similar roles may be very important to consider. The opposite is very clear, too. Gender, ethnicity, and age should have no legitimate bearing on someone’s job performance. This next point is critical. A hiring manager cannot meet an applicant in an interview and credibly say that they don’t recognize the gender, ethnicity, or general age category of the person sitting across from them. No matter our intentions, this is incredibly hard to do. Conversely, it is the easiest task for an algorithm to perform.

If the algorithm is not provided gender, ethnicity, or age, there is no chance for those variables to be brought into the hiring decision. This involves bringing in the data that is germane, having a computer look at what hiring decisions have been made in the past that have resulted in high performing long-term employees, and then strengthening future decisions based on the past performance of good hiring management practices. This will ultimately remove the bias in hiring.

One of the things that deserves consideration is the idea of perpetuating past practices that could be biased. If all we are doing is hiring like we have hired in the past and there have been prejudicial or biased hiring practices, that could promote institutional bias.  Through time, we have trained computers to do exactly what a biased manager would have done in the past.  If the only data that is used (“trained”) for hiring is the same data that is selected by biases of the past, then it is difficult to train on data that is not biased. For example, if we identify gender as a bias in the hiring process, and we take the gender variable out of the algorithm, gender would not be considered. When we flag previous bias, we are able to minimize future bias.

We should unabashedly look at whether we are able to identify and learn from hiring practices that may have had bias in the past. This is one of the greatest strengths of applying very simple machine learning algorithms in the area of hourly hiring.

What if an explicit goal is diversity? Can we still hire the best?

An aspect of the hiring process that opens up a lot of opportunities in the area of artificial intelligence and machine learning is implementing diversity.

Artificial intelligence can really differentiate itself here. Machine learning can make the very best hiring decisions based on the data that it’s given; if you have diversity goals and want hiring practices to encourage a diverse work population, it is very simple to choose the best candidates from whichever populations are important to corporate goals. This can be done transparently and simply. It doesn’t prioritize one person over another. It allows the hiring of the very best candidates from each population that you’re interested in representing the company.

Upon scrutiny and scientific examination, machine learning can be a very valuable tool for augmenting the hiring decisions managers make every day and help to understand when bias has entered into our decisions and yielded far less than our collective best.

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