Category Archive: Uncategorized

Shortly, even the CEO will be outsourced to an online labor marketplace

Over the past decade, there has been a ferocious rise in the freelance economy in the United States. Millions of people today work on platforms ranging from Uber and Lyft to Taskrabbit and Fiverr, accepting what are usually short-term tasks that can be completed efficiently and repeatedly. While these casual jobs have been the focus of intense scrutiny about their pay structures and work security, their effects have been mostly limited to talent not engaged in business professions.

Times are quickly changing, though, and marketplaces are increasingly entering white collar territory with better product design.

Take for example Clora, which works with the highly-specialized talent required to produce and launch a new life sciences product. Or Paro, which connects businesses to bookkeepers and other financial professionals to manage a company’s finance department. Or Catalant(formerly HourlyNerd), which works with independent business consultants who can solve a range of complex problems like market sizing or product marketing.

It might be an exaggeration, but it is only a matter of time until rent-a-CEO options exist as well.

Part of this transformation of white collar work certainly comes from companies and workers desiring more flexible work arrangements. However, I would also argue though that renewed focus on product design has been critical for effectively building a marketplace for online talent.

Different tasks often have wildly different requirements and workflows, and the product needs to match the kinds of talent it hopes to attract. These newer marketplaces understand that professional work is often ambiguous and hard to judge for quality, and have built key product features to handle those challenges.

That’s very different from the early years of the consumer internet, when online labor marketplaces were designed as free-for-alls, with both sides of the market competing for transactions to occur. A customer might post a potential job to Craigslist, or a worker might post their availability to be hired. These were marketplaces built around serendipity, with almost no guidance from the platform on what to charge, how to charge, or how to find the best talent for a particular project.

Over time, it became clear that some tasks were much more popular than others, and they were quite repeatable as well. Uber takes a passenger from one origin to one destination, and Taskrabbit allows you to hire someone to install IKEA furniture. You don’t need to use paragraphs to describe what you are looking to do, nor should you have to negotiate a price every single time you want to get into a car or get a MALM bed frame installed.

That regularization became the product itself — suddenly the free-for-all marketplace became a tight menu of options with standardized pricing and rating systems. Even more importantly, the identities of the workers themselves are often shielded from the customer on these platforms. You are buying the company’s brand of quality, not the worker’s guarantee that they can do the job.

There is a marketplace today for pretty much every simple and easy-to-define task imaginable. The challenge has been how to design marketplaces to handle more complex forms of work and evaluate the quality of that labor, particularly in cases where quality can be in the eye of the beholder.

One answer has been to focus on hyper-specific (yet lucrative) verticals. Clora and Paro are good examples of this trend. Clora’s strength is knowing the hiring model for the pharmaceutical and life sciences industry. They understand what talent is needed, and even more importantly, how to evaluate that talent. By focusing on accounting, Paro has a relatively objective standard on what quality work looks like, and that makes evaluation a bit easier.

The key to each of these platforms is that pricing, ratings, quality, and product offerings are not standardized in the same way as the productized marketplaces that came before. Each of these platforms recognizes that, say, the launch of a cancer drug is going to be very different from a male-pattern baldness therapeutic. There is no secret algorithm that is going to be able to detect these nuanced differences without human judgment entering the equation.

So to compensate for that variability, these marketplaces put much more of the judgment around the quality of work on the shoulders of the professionals themselves. Unlike Uber, there is no GPS telling someone to move from this work to that work. As such, these newer marketplaces are something of a hybrid between the first-generation free-for-all Craigslist-style marketplaces and the second-generation productized ones like Uber we have seen more recently.

B12, a company I profiled recently, is trying to build a unified infrastructure for handling exactly these sorts of ambiguous jobs. Its open-source Orchestra platform is designed to handle not just the non-linear work patterns that arise in these contexts, but also how to judge quality on the platform (it’s answer is to have professionals evaluate other professionals). It’s an audacious idea, although I still believe we will see many virtualized marketplaces since sales and marketing into these each of these industries is challenging.

When we really evaluate what is happening around work, particularly professional work, there can be incredible complications that make machine learning and algorithms hard to execute. Product designers need to include the ambiguity, complexity, and social human factors into labor marketplaces to properly attack these industries. Thankfully, we are seeing a new crop of startups do exactly that, and that will not just provide opportunities for founders and VCs to make a bunch of money, but potentially millions of more workers as well.


via:  techcrunch

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Google Search comes to iMessage

Google Search is now available within iMessage. In an effort to more deeply integrate Google’s search engine on iOS devices, the company announced today that its Search app for iOS has added an iMessage extension, allowing iPhone and iPad users to search the web, then quickly add those search results to their iMessage conversations.

The extension itself is clearly inspired by Google’s experiments with Gboard, Google’s own third-party keyboard app for iOS devices, and comes at a time when the popularity of alternative iOS keyboards seems to be declining. Nuance, for example, just shut down its Swype keyboard app; and Swiftkey had exited to Microsoft a couple of years ago.

With Google’s iMessage extension, users can type a query in the search box, or tap a button below for a specific type of search – like Weather, Food, Nearby (venues/businesses), Trending (news), or Videos – all very similar to Gboard.

Google highlights restaurant search in particular in its announcement, as deciding where to eat is a common theme in iMessage chats. Tapping “Nearby” can help quickly pull up business listings or points of interest near your current location, which is also useful when communicating about a particular location.

Each search result includes a “Share” button that, when tapped, adds the item directly into an iMessage conversation as card. When the recipient taps on the card, they’ll go to the Google search result.

In addition, Google’s iMessage app offers a GIF search engine. This is available by tapping on the “GIF” button to the right of the search box, which will immediately load a selection of GIFs from sites like Giphy and Tenor, which you can then filter further by performing a search.

GIF search is a popular feature in Gboard, following that app’s update last year.

Making Gboard’s features available via an iMessage extension makes sense because not everyone wants to swap out their default keyboard on their iOS device.

It also give Google another way to reach users on iOS, even when they’re not in Google’s app itself. This is important because Google’s traffic acquisition costs have been climbing due to the shift to mobile devices, where apps and assistants like Siri serve up many of the answers users once turned to Google for, when on desktop. It also has to pay Apple billionsto be the default search engine on iOS.

The app, like other iMessage extensions, is available by tapping the iMessage apps drawer in iMessage, then scrolling over to the Google app icon. (If you have a lot of iMessage apps already installed, it may be tucked away under “More.”)

The iMessage extension is one of three new features Google announced today for iOS users. However, it has actually been available in the Google app since February 7, 2018, according to Sensor Tower, indicating more of a soft launch.

Google also added two other features that integrate its search engine into iOS in new ways. One is a new share sheet option – now, when you share a webpage from Safari with Google, it will also show you suggestions for related content. A similar feature launched last year in the Google Search app, but is annoying as it pops up over the content when you reach the bottom of the page. With the new Share with Google functionality, it makes a bit more sense as the idea is that you could move from a webpage in Safari directly into a set of Google search results on the topic/

Also new is support for drag and drop on iPad. You can use the feature to move text, images, and links to and from the Google app, share articles from Google into iMessage, or save them into Notes for later reading.

All features are available today, but the iMessage extension is currently U.S.-only, Google says.


via:  techcrunch

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Amazon is buying smart doorbell maker Ring

With Nest’s first smart video doorbell right around the corner, Amazon is busy buying up the competition.

After acquiring Blink just two months ago, Amazon is now acquiring Ring, makers of the self-titled Ring doorbell (plus a bunch of other security gear, like solar security cameras, floodlight cams and an in-home alarm system).

GeekWire broke the rumor this afternoon, and we’ve just received independent confirmation.

Details on the deal are still pretty light; the financial terms of the deal, for example, haven’t trickled out just yet. Update: Reuters is reporting, via tweet, that the sale price was more than $1 billion. The company had raised around $209 million to date, according to Crunchbase.

This acquisition makes plenty of sense. Amazon has already built a few connected cameras of its own — but hardware is, as they say, hard, and that’s not going to change. With nearly a dozen solid products to its name, the Ring team has proven themselves more than capable of building hardware (and I’m sure its array of patents doesn’t hurt, either.) With Amazon, Google, Apple et al. all duking it out for physical space in and around your home, someone was going to make a big offer — and I’d be surprised if Amazon was the only bidder in the mix. Plus, who on earth is responsible for more doorbell presses than Amazon?

(Fun bit of trivia: Ring debuted to the world on Shark Tank back in 2013, then known as “DoorBot.” They wanted $700,000 for 10 percent of the company, but no one took the deal.)


Via:  Techcrunch

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84% of cybersecurity pros are open to switching companies in 2018

Cybersecurity workers say they are seeking workplaces that take their opinions seriously more than those that offer a high salary, according to (ISC)².

As demand for cybersecurity professionals continues to grow, those with the coveted skillset are looking for workplaces that offer more than just a large salary, according to a new report from (ISC)².

Of the 250 cybersecurity pros surveyed across the US and Canada, 14% said they plan to search for a new job in 2018, while 70% said they are open to new job opportunities, the report found. Just 15% said they have no plans to switch jobs this year.

The data suggests that unmet expectations between companies and their cybersecurity workforce during both the hiring process and time on the job, combined with high demand for security skills and frequent contact from recruiters, may be luring cybersecurity pros away from their current workplace.

“The cybersecurity workforce gap is growing rapidly, and turnover within cybersecurity teams makes filling those roles even more challenging,” (ISC)² COO Wesley Simpson said in a press release. “It is more critical than ever for organizations to ensure their recruitment and employment retention strategies are aligned with what cybersecurity professionals want most from an employer.”

When asked what’s most important for cybersecurity pros’ personal fulfillment at work, the top response (68%) was wanting to work where their opinions are taken seriously, the survey found. Other top drivers were wanting to work where they can protect people and their data (62%), wanting to work for an employer that adheres to a strong code of ethics (59%), and wanting a high salary (49%).

In terms of professional goals, 62% of cyber pros said they want to work for a company with clearly defined ownership of cybersecurity responsibilities, while 59% said they want an employer that views cybersecurity more broadly than just technology. Another 59% said they want to work for an organization that trains employees on cybersecurity best practices.

Due to demand, cybersecurity workers are being aggressively targeted by recruiters: 13% said they are contacted by recruiters many times a day, while 8% said once a day, 16% said a few times a week, and 34% said a couple times each month.

Employers often fail to impress cybersecurity jobseekers and staff, the report found. An organization demonstrates a lack of cybersecurity knowledge to a cyber pro when it offers vague job descriptions (52%), job descriptions that do not accurately reflect the role responsibilities (44%), and job postings that ask for insufficient qualifications (42%).

Before taking a job with a new company, 85% of cyber pros said they would investigate that employer’s security capabilities—and that what they discover would influence their decision. More than half of respondents (52%) said that they are more likely to take a job with an organization that takes security seriously.


via:  techrepublic

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Google’s DeepMind and the NHS: A glimpse of what AI means for the future of healthcare

The Google subsidiary has struck a series of deals with organizations in the UK health service — so what’s really happening?

Healthcare has always been seen as rich pickings for artificial intelligence: when IBM first decided to kit out Watson for use in the enterprise, its earliest commercial test was in cancer care.

There are a number of reasons why health and artificial intelligence might seem like a good fit.

One is simply that healthcare organizations around the world, and in the UK in particular, need to save money: any task that can be taken off a clinician’s workload and automated by AI potentially represents a cost saving.

What’s more, healthcare has loads of data — test results, scans, consultation notes, details of appointment follow-ups — most of which is unstructured. For AI companies, that means lots of material that can be used to train up AI systems, and for healthcare providers, it means a lot of data that needs organizing and turning into usable information.

For an NHS under pressure to deliver better healthcare at lower cost, the lure of AI will prove hard to resist.

Take the agreements between Google subsidiary DeepMind and the likes of Moorfields Eye Hospital and University College London Hospitals (UCLH) Trust: both pave the way for a future where the routine work of reading scans is done by an algorithm rather than a healthcare professional, leaving clinicians more free time to attend to patients.

The deals lay the foundation for greater use of AI in the NHS by providing data that DeepMind can use to train up its algorithms for healthcare work. In the case of Moorfields, a million eye scans along with associated information about the conditions they represent will be fed into the DeepMind software, teaching it how to recognize eye illnesses from such scans alone in future.

Under the UCLH deal, 700 scans of head and neck cancers will be given to DeepMind to see if its AI can be used in ‘segmentation’, the lengthy process whereby the areas to be treated or avoided during radiotherapy are delineated using patient scans. Currently, it’s a process that takes four hours — a figure that the DeepMind and the trust claim could eventually be cut down to one hour with the use of AI.

It’s not quite clear who will be benefitting most from these deals: DeepMind or the NHS. Moorfields’ scans will allow the Google subsidiary to improve the commercial viability of its systems, by improving the accuracy with which it can detect particular eye diseases — potentially making a commercial version of the software a must-buy for the hospital. However, according to a freedom of information (FOI) request filed by ZDNet, there has been no deal agreed between the two organizations to roll-out the software once it’s trained up, and DeepMind is only paying Moorfields for the staff time involved in processing the data before handing it on to the AI company.

It’s a similar story with UCLH: “The collaboration between UCLH and DeepMind is focused on research with the goal of publishing the results. There are currently no plans for future rollouts… DeepMind is not providing financial compensation to UCLH for access to data. DeepMind will support the costs of UCLH staff time spent on the de-identification and secure transfer of data,” UCLH said in response to an FOI filed by ZDNet.

Both trusts have already made clear that they, rather than DeepMind, remain the data controller and that ownership of the scans remains with them. DeepMind for its part will appoint a data guardian to control who has access to the scans, and will destroy the data once the agreement ends.

The need to champion good data hygiene likely comes from an earlier deal DeepMind made with the Royal Free NHS Trust, which came in for a good deal of criticism over its handling of patient data.

After a New Scientist investigation revealed that the details of 1.6 million people were being made available to DeepMind — including data over and above that which related to acute kidney injury — the Information Commissioner’s Office began an investigation into the pair’s arrangement. It was also recently criticized in an academic paper, Google DeepMind and healthcare in an age of algorithms, which said “the collaboration has suffered from a lack of clarity and openness”, adding: “if DeepMind and Royal Free had endeavored to inform past and present patients of plans for their data, initially and as they evolved, either through email or by letter, much of the subsequent fallout would have been mitigated”.

The Royal Free entered its agreement with DeepMind last year, when it announced it would be using an app called Streams to identify people who could be at risk of acute kidney injury. By keeping tabs on patients’ blood test results and other data, the DeepMind system can alert clinicians through the Streams app on a dedicated handheld device about when patients are experiencing a deterioration in their condition, and so aid medical staff to take preventative action.

The system was first used with live patient data in January of this year, the Royal Free Trust told ZDNet in response to an FOI. Up to 40 clinicians will be using Streams in the first phase of the rollout, and “the implementation will be phased across all Trust sites starting with the Royal Free Hospital”.

A similar agreement with the Imperial Trust looks to be more of a slow burner than the Royal Free’s: when the trust announced the Google deal, it said it had signed up for an API that would allow data to be moved between electronic patient record systems and clinical apps, be they DeepMind or other companies’.

The trust did note that the deal would cover the eventual rollout of Streams. In response to an FOI request by ZDNet, Imperial said it will begin piloting Streams app in either April or May, and the trial is currently working its way through the Trust’s governance processes for technical and clinical approval.

As a result, Imperial said it couldn’t provide details of where Streams will be piloted and by how many staff, but added it will be used “in a limited environment and in parallel with existing response processes and procedures”.

It also appears to not be following in the footsteps of the Royal Free when it comes to functionality just yet, saying the initial deployment won’t use the alerting facility and so there have been no targets set around when staff should respond to any alerts sent.

Interestingly, given DeepMind is best known as an AI company, there is no whiff of AI used in Streams, as Imperial’s website makes clear, saying: “this partnership does not use artificial intelligence (AI) technology and the agreement between the Trust and DeepMind does not allow the use of artificial intelligence”.

Streams is, according to Gartner analyst Anurag Gupta, more akin to standard issue analytics software than AI.

“Streams has nothing to do with AI at this point in time. It basically collects information from a few different systems, it then uses NICE’s proprietary algorithm on top of that… and it presents information from multiple systems in an easy to understand format. It’s common sense. It’s more like business intelligence.”

While DeepMind’s work with the UK’s health service seems to have attracted a great deal of headlines — many of them negative — there’s no doubt that we’ll be seeing more artificial intelligence in healthcare in general and in the NHS in particular. Anecdotally, the non-AI Streams app has already been saving hours of nurses’ time, and the benefits of such systems could potentially be even greater once AI has been properly brought to bear. Used well, with proper data governance, patient buy-in, and competition among AI providers, it can help the NHS deliver better patient care by freeing up clinicians from some of the more mundane tasks.

“In the short term, our skills and the AI’s skills are complementary: things that AI systems can do very well, crunching a lot of information, making sense of a lot of information in a narrow domain, doing things in a repetitive fashion — that work can be done by AI, and [humans’ skills] can sit on top of that AI, because we are much better in building the context to that information,” Gupta said.

Diagnosis, he adds, is “part science and part art”. Artificial intelligence can provide the former, but only human intelligence can do both.


via:  zdnet


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65% of organizations will fail to meet critical GDPR compliance by deadline

The May 25 deadline for the EU’s General Data Protection Regulation (GDPR) is fast approaching, and all companies in the EU as well as those that deal with EU residents must comply with new data privacy laws, or face a fee. However, 65% of organizations are still not confident that their GDPR data will stay within the EU, according to a Tuesday report from Solix Technologies.

A recent UK government report found that less than half of businesses are aware of the upcoming GDPR laws, or what they mean for how information security is handled, as reported by ZDNet. This could pose a major financial problem for businesses, as non-compliance can result in fines of up to 4% of a company’s global annual revenue, or €20 million, whichever is higher.

Today, 22% of organizations said they are unaware that they must comply with GDPR, even if they are based outside of the EU but hold data of EU citizens.

“Based on our survey data, it’s clear that the majority of organizations are not currently prepared to meet GDPR requirements,” John Ottman, executive chairman of Solix Technologies, said in a press release. “There is an urgency to take steps now, as the enforcement deadline quickly approaches and applies to anyone who is currently operating with EU customers.”

Confusion still reigns over the GDPR’s “right to be forgotten,” as noted by ZDNet. This right allows an individual to request the deletion or removal of personal data when there is no longer a “compelling reason” for it to exist, according to the UK’s Information Commissioner’s Office.

Some 65% of organizations said they are unsure if an individual’s personal information is purged from all systems, forever, under this rule, the Solix report found. And 53% of organizations said they are not confident that processing of all personal data is based on explicit permission provided by the individual.

Further, 38% of organizations said that all their personal data under the new GDPR rules is not protected from misuse and unauthorized access at every stage in its lifecycle. And while 82% of organizations said they know where their sensitive data is stored, only 55% maintain audit trails for data consents, collections updates, and deletion.


via:  techrepublic

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Microsoft rolls out more AI-infused healthcare services, software

Microsoft’s year-old Healthcare NExT research organization is stepping up its work to make Microsoft’s cloud and AI services applicable to health researchers and doctors.

While Amazon and Apple are looking at healthcare from the employee-consumption side, Microsoft is focusing on using its cloud assets to meet the needs of researchers and doctors.

Last February, Microsoft announced it was creating a new healthcare-focused research unit, Healthcare NExT. On February 28, a week ahead of the HIMMS (Healthcare Information and Management Systems Society) medical IT conference, Microsoft is rolling out more healthcare “intelligent health” services and software.

Microsoft is making its Microsoft Genomics service generally available as of today. This service, which runs on Microsoft’s Azure cloud, is a precision medicine/genomic-processing service for medical professionals. Microsoft additionally is making generally available as of today its Azure Security and Compliance Blueprint for HIPAA/HITRUST. This guidance document is designed to help health organizations move to Azure while handling sensitive data.

Microsoft also is publishing new developer templates under the “Microsoft 365 Huddle Solution” brand. These templates are for Microsoft Teams and meant to enable health professionals to better use Teams in creating and maintaining their workflows. And the company is working on a research collaboration with UMPC to create a “Project Empower MD” system to reduce the task of note-taking for physicians.

Microsoft made its initial foray into healthcare over a decade ago, but ended up retrenching and selling off most of the health assets it originally acquired. Recently, the company announced it was dropping its HealthVault Insights applications, but is applying lessons learned about increasing patient engagement using machine-learning to other healthcare initiatives, officials said.

While Microsoft continues to operate its HealthVault patient-records system, the focus for the Healthcare NExT organization is first and foremost about applying the huge amounts of cloud processing power and AI smarts to the growing amount of health data out there.

“We make equity investments, we do commercial agreements, but we are very research-focused,” said Peter Lee, Corporate Vice President and head of Healthcare NExT “We are not a profit and loss center for Microsoft. This organization was Satya’s (CEO Satya Nadella) and Harry’s [research chief Harry Shum] idea.”

Lee said his ultimate challenge is to harness all of Microsoft’s AI products and services and turn them into viable health services. But don’t expect Microsoft to use the same tactic to create a Retail NeXT or Insurance NExT research organization. Healthcare got the spotlight because, at least in part, of Microsoft’s increasing and very public mission of doing good.


via:  zdnet

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Report: 52% of companies sacrifice security to expedite projects

Businesses can be exposed to vulnerabilities when professionals prioritize a deadline over security, according to research from Threat Stack.

More than half of companies admit to loosening security measures to expedite projects or meet deadlines, a new Threat Stack report found.

In a survey of over 200 executives, 52% said their company had prioritized a deadline or objective over the firm’s security. The emphasis on speed over security could leave holes in a project, leaving a company vulnerable.

The focus on speed comes from pushback on both sides of a project, the report found. Over two-thirds—68%—of respondents said their CEO asks the DevOps and security teams to not do anything that would slow a project, while 62% said their operations team sometimes fights new security efforts.

he majority of respondents said SecOps is important for their organization, but only 35% said it was a complete or mostly complete project at their company. At 18% of companies, SecOps isn’t established at all, the report found.

“The vast majority of companies are bought-in, but, unfortunately, a major gap exists between intent of practicing SecOps and the reality of their fast-growing businesses. It’s important that stakeholders across every enterprise prioritize the alignment of DevOps and security,” Brian Ahern, Threat Stack CEO, said in the press release.

Most of the challenges come from organizational alignment, the report found, as DevOps and security teams might be operating in different silos.

The discrepancy suggests companies should agree and focus on security to ensure their company remains safe, even under pressure from a deadline or the competition.


via:  techrepublic

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How one AI company is bringing medical care to millions of rural Chinese residents

Providing health services to a widely-dispersed population can be a challenge. Here’s how AI can help when there aren’t enough medical professionals to go around.

China’s population, which in 2016 had 793 million urban residents and 590 rural residents, is spread out over a land mass of 3.7 million square miles.

By 2010, 93% of the rural population had healthcare coverage, but providing rural medicine and timely healthcare to rural regions persist. This is where analytics can make a difference.

“We wanted to take analytics, artificial intelligence and deep learning technologies and use them to better understand different medical conditions, how to diagnose them, and how to treat them,” said Kuan Chen, founder and CEO of Infervision, a Chinese artificial intelligence and deep learning company that specializes in medical image diagnosis.

Analytics, artificial intelligence, and deep learning are put into play by analyzing medical images and reports on different pathological conditions, and then coming up with different models and sources of treatment and medical interventions based on common patterns that are assembled from studies of thousands of patients in China’s urban hospitals. “These models use deep learning to ‘learn’ from the data and continuously improve their diagnostic capabilities,” said Chen.

The first disease that Chen targeted was lung cancer, with the software being able to locate hard-to-detect or hidden nodules in the lungs that could prove to be cancerous.

Now the task at hand is providing a similar diagnostic and medical intervention tool for strokes, which can especially be useful in rural areas where qualified medical practitioners are scarce.

How important is this?

“In many rural areas in China, there are no trained radiologists who can help stroke victims,” said Chen. “And in other areas of the world, like the US, radiologists make an average of $375,000 a year, so they are very expensive.”

Chen says that the feedback he gets from hospitals is that younger radiologists and medical practitioners rely heavily on AI, while older practitioners prefer to use it as a second opinion that they cross-check against their own.

“In a stroke, you want to respond to the condition as quickly as possible,” said Chen. “It might take 30 to 35 seconds in a standard process to generate a report on the condition so treatment can be determined. With our tool, that time is cut to less than three seconds.”

The use of deep learning and expanded analytics also expand the spectrum of diagnosis, which can lead to better results.

“In one non-stroke case that involved diagnosis and treatment of a bone fracture and a degenerated area of bone, the standard approach is to treat the affected area itself,” said Chen. “With analytics and AI, a system can focus on different areas of the body that are far removed from where the problem is to see if these other areas could be affecting the condition. If it is a problem that is being generated far from the fracture itself, the analytics allow us to treat causes of the condition, and not just symptoms.”

Here are some best practices hospitals and clinics can adopt as AI and deep learning tools evolve:

Deploy the tool where help is needed most

If there is an acute shortage of medical practitioners in a specific region, analytics and AI can help in situations like stroke intervention and treatment, and the chances for success for patients will improve.

Use the tool for training

Radiologists and medical practitioners must develop knowledge and experience before they can become expert diagnosticians. An analytics and deep learning tool can assist in the training process because users can compare their own findings against what the system finds in numerous scenarios.

Learn to expect the unexpected

You might think you are going to treat one condition and end up treating another. The bone fracture that Chen mentioned, where the system actually found the causal problem in a different area of the body, is a prime example. This is why medical practitioners should keep their minds open.

Never forget that AI and deep learning tools are still developing

Just because a system uses AI, deep learning and analytics doesn’t mean that is it always right. Medical practitioners should use these systems as assistants and not as undisputed authorities, because there are some areas where a machine can’t be a replacement for human thought and reasoning.


via:  techrepublic

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46% of orgs never change cybersecurity strategy, even after attack or breach

Security professionals still struggle to prevent attackers from breaking into internal networks, according to a CyberArk report.

Despite an increasingly sophisticated cyber threat landscape, organizations are failing to proactively update their security defenses, according to a new report from security firm CyberArk. Some 46% of the 1,300 IT professionals and business leaders surveyed said that their organization’s security strategy rarely changes substantially, even after suffering a cyberattack.

Further, 46% of security professionals said that their organization can’t prevent attackers from breaking into internal networks each time a hack is attempted, the report found. And only 8% of security leaders said that their company continuously conducts penetration testing to determine where vulnerabilities may sit.

“In medium to large organizations especially, there is a need for security teams to reset expectations around where security priorities and spend should be focused,” the report stated. “These findings support the dangers of inertia, with organizations not taking the initiative to make necessary changes following an attack.”

Organizations are also failing to protect privileged credentials and data in the cloud, the report found. While 50% of IT professionals said their organization stores business-critical information in the cloud, 49% said they have no privileged account security for the cloud—so they are storing data in the cloud, but not taking additional steps to protect it.

In terms of protecting passwords, 36% of companies reported that administrative credentials were stored in Word or Excel documents on company PCs, 34% said they were stored on shared servers or USB drives, and 19% said they were stored on printed documents in physical filing systems.

Many organizations are also failing to adequately protect endpoints, the report found: Only 52% of IT security professionals said they keep their operating systems and patches current, and 29% employ whitelist application controls.

As professionals reported the greatest security threats facing their organization are targeted phishing attacks (56%), insider threats (51%), and malware and ransomware (48%), it’s important for companies to remain vigilant about cybersecurity best practices.


via:  techrepublic

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