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Supercomputing | newsIBM Launches 'huge statistics' Bootcamps in Universities
Now that Watson has had its newest resurgence of repute and looked as a correct trending subject on each Google and Twitter, IBM is set to display school students the way to use the underlying applied sciences of the supercomputer. In a push called "huge information," the business will promote bootcamps on suggestions administration of big quantities of statistics via institution locations, IBM innovation facilities, and online.
The camps, which are free, will final from three to five days and take place in lecture room settings. anyway college students, the business has invited IT authorities to take part. on the conclusion of periods, individuals could have the opportunity to take free technical mastery exams and IBM certification exams.
Bootcamp classes will cowl discrete areas, including using IBM facts management utility similar to DB2, pureXML, Informix, InfoSphere Optim and Guardium, and open source functions Hadoop and Eclipse. college students will acquire training in administration and analysis capabilities for huge records environments, including information federation, integration, and warehousing concepts, as well as facts administration planning, and facts governance, nice and protection techniques.
the new initiative follows on IBM's Watson Jeopardy! victory, where the computing device confirmed how synthetic intelligence can work in the real world (at the least within the actual world of a online game exhibit). The equipment includes ninety clustered IBM vigour 750 categorical servers, a potent build-up of hardware that may opt for via 500 gigabytes of information a 2d.
but IBM referred to that as extra agencies movement to similar systems to address their large statistics challenges, a competencies hole is surfacing.
"corporations are gathering up to petabytes of assistance during height hours of operations, and they see an opportunity to make use of this data to profit new insights into their purchasers and get forward of the competition," stated Arvind Krishna, general manager of IBM tips management. "Uncovering insights hidden among facts in latest IT programs, and outside of the firewall in social networks, on clouds, and from cell contraptions, requires trendy IT specialists to possess new talents."
Mahatma Gandhi Mission's college of Engineering & technology in India these days launched campus workshops on DB2 for its engineering students and college. currently, more than 600 college students and college participants are certified and trained on IBM technologies.
"IBM is bringing actual world business event to college students to keep them involved with emerging applied sciences and IT trends equivalent to huge facts," observed Professor Nareshkumar Harale, head of laptop Engineering. "When universities and agencies collaborate, they construct the subsequent technology of professional guidance know-how leaders to create new opportunities, gas economic increase and remedy challenges that may enhance the style they reside."
Dian Schaffhauser is a senior contributing editor for 1105 Media's training publications THE Journal and Campus technology. She will also be reached at firstname.lastname@example.org or on Twitter @schaffhauser.
September 08, 2008 12:05 ET
greatest advice Infrastructure Launch Ever for IBM; New offerings permit purchasers to address guidance Challenges and circulation records From associations to people and "Clouds"
MONTPELLIER, FRANCE and ARMONK, the big apple and TOKYO--(Marketwire - September eight, 2008) - IBM (NYSE: IBM)
IBM these days introduced its largest launch ever of new storage hardware, software and services which are the constructing blocks for the area's strongest assistance infrastructure portfolio. the new IBM offerings are designed to permit groups, governments and different associations to radically change static information managed in silos into more dynamic counsel it is purchasable by way of individuals wherever they go in a cloud computing environment.
As buyers now appear to "take their suggestions" with them -- improving their healthcare, security, amusement, social life and purchaser event every time, everywhere, in real time -- agencies are fighting out of date facts centers, which are unable to deal with the expanded suggestions management demands.
The proliferation of the mobile internet, linked sensors far and wide, from cars to pipelines, on-line scientific statistics, and the explosive boom of net 2.0 information and social networking, is resulting in sixteen-fold growth in each particular person's "assistance footprint" with the aid of 2020, in line with IBM. Infrastructures should adapt nowadays to meet this demand. To hearken to an IBM podcast on tips infrastructure click on: here.
In response, IBM today delivered vital points for an guidance infrastructure as part of its New commercial enterprise data core strategy. These points center of attention on the provision, compliance and retention, and protection ache points for shoppers as they re-design their facts centers. more than 30 new and upgraded products and services are being added across the IBM portfolio to fulfill these essential needs: To take heed to an IBM podcast on these new offerings click: right here.
internet-Scale Availability: state-of-the-art infrastructure is not designed to effectively control the estimated two billion people who may be on the web by using 2011(3) nor the expected 1000000000000 linked objects -- automobiles, appliances, cameras, roadways, pipelines -- comprising "the cyber web of issues." reasonably priced, scale-out technologies are essential as a necessary factor of a shopper's suggestions infrastructure to enable cyber web scale and pace for the administration of substantial quantities of online guidance within an organization and out to billions of individuals. companies ought to be prepared for this new phase of "cloud computing," giving patrons entry to statistics and programs remotely, from any equipment, anywhere. to fulfill these wants, IBM introduced a collection of products and offerings enabling cyber web Scale Availability. among the many highlights:
Consolidation and Retention: modern day suggestions infrastructure suffers from large inefficiency in each reproduction sources of the same suggestions and excessive power expenses. leading analysts have stated that fifty p.c of records facilities will run out of energy or house for their records centers someday in 2008(4) and the power consumed by U.S. information centers will develop from 1.5 p.c to 2.5 percent of the nation's complete power consumption over the subsequent 5 years.(5) to fulfill these wants, IBM announced a series of products and choices enabling information core consolidation and retention. among the many highlights:
safety: ensuring that the tips in a knowledge middle is comfy and being accessed best by way of these authorized has develop into a properly subject for all facts facilities -- tremendous and small. A recent information core hack can charge one company more than $60 million bucks in damages through theft of facts and unauthorized use of bank card guidance of consumers.(9) in the meantime, the provision and authentication of records -- from huge corporate and executive databases to the 1 billion people anticipated to be the use of the cell net(10) this year -- is a key precedence.
greater than 30 new products and features from IBM systems and expertise community, IBM software group and IBM research were introduced these days, aiding the tips infrastructure pillar of IBM's New enterprise information core method. Coupled with new bulletins from IBM's global expertise services company, IBM aligns crucial storage utilization to a client's direct company priorities, helps them cut back the chance, can charge, complexity and planning efforts required for giant data migrations, and gives you strategic IBM design and implementation functions to target client pain-elements. For a full listing of all the items and capabilities introduced today, please seek advice from http://www.ibm.com/programs/storage/products/exhibit/index.html
via home-grown innovation, building and acquisitions, trendy announcement marks a $2 billion investment, three years of research and building, and a world group of greater than 2,500 storage technical gurus, engineers and researchers from nine diverse international locations together with France, Germany, Israel, Japan, Mexico, Singapore, Switzerland, united states, and the UK. Key acquisitions of XIV, Diligent, Cognos, Arsenal, Optim, FilesX, Softek, and NovusCG over the ultimate 24 months add strategic items to the strongest ever counsel infrastructure portfolio of choices unveiled these days. For a timeline on IBM's storage acquisitions and subsequent-era technologies from IBM research being developed to increase future information infrastructure choices, click on on http://www-03.ibm.com/press/us/en/pressrelease/25035.wss
"the realm is re-tooling its underlying IT infrastructure in a dramatic shift faraway from a a long time-historic customer/server mannequin to a radically greater productive information superhighway-trend architecture. This requires diverse pondering and new capabilities, which they are addressing during this advice infrastructure launch, with their investments going forward, and the way IBM will do enterprise with their customers," observed Andy Monshaw, customary manager, IBM equipment Storage. "There isn't any bigger probability for their customers than to unencumber the price they have in their data facilities and support them create sensible, imaginitive choices for his or her conclusion clients -- the buyer. IBM is the most effective enterprise in the world -- not HP, not EMC, now not solar -- with decades of analysis, industry skills and market management to make this a reality for their consumers."
To assist valued clientele speed up their statistics core transformation initiatives and combine these new IBM counsel infrastructure choices into their records facilities, IBM is also asserting the global opening of the brand new enterprise data middle management centers. At these new centers, greater than 500 IBM engineers and consultants across areas in the U.S. and Europe will work with customers and center of attention on options and premiere practices around power effectivity, consolidation and virtualization, business resiliency and protection and repair administration and tips infrastructure. greater tips can be found right here: http://www.ibm.com/support/techdocs/atsmastr.nsf/internet/leadershipcenters
These new equipment and offerings for the IBM assistance infrastructure will allow purchasers to streamline their records centers with tremendously built-in storage choices focused around archive, compliance, retention, and protection ache facets to aid valued clientele bring information as a carrier to their customers -- the patrons, who are searching for entry to assistance at any time from any gadget. These tools and expertise resources which IBM has been constructing and gathering, open doorways to new trade collaborations, and on demand storage technologies -- a key pillar in the emergence of cloud computing.
IBM global Financing, the lending and leasing business segment of IBM, offers low-fee financing and environmentally safe storage asset disposal for this comprehensive suite of latest suggestions infrastructure offerings. IBM international Financing prices are as low as four.6% for hardware purchases; 4.8% for software; and 6.three% for services for optimal qualified customers. For assistance on convenient funding options for customers in search of to finance these new storage expertise capabilities, visit: http://www-03.ibm.com/press/us/en/pressrelease/25037.wss
For more suggestions about IBM, IBM gadget Storage and the IBM assistance Infrastructure, visit http://www.ibm.com/information_infrastructure
IBM, system Storage, and the IBM emblem are trademarks or registered logos of overseas business Machines service provider. For an inventory of extra IBM emblems, see www.ibm.com/felony/copytrade.shtml(1) supply: IBM internal (2) source: IBM interior (3) source: "worldwide web users desirable 1 Billion in 2005." computing device business Almanac. four Jan. 2006. 30 July 2008, http://www.c-i-a.com/pr0106.htm (four) supply: EPA document to Congress on Server and records center effectivity, introduced on August 2, 2007 (5) supply: November 29, 2006 press unlock: "Gartner Says 50 p.c of statistics facilities could have insufficient vigour and Cooling capability by means of 2008": http://www.gartner.com/it/page.jsp?identification=499090 (6) source: Gartner's "Cool companies In facts insurance plan, 2008." identification quantity: G00155726 (7) source: As of September 3, 2008. Comparisons are according to posted information when evaluating highest tape cartridge slots per square foot. The IBM TS3500 with LTO can dangle a hundred twenty five. http://www-304.ibm.com/jct03004c/systems/storage/tape/ts3500/requisites.html The sun SL8500 can dangle 72. http://www.sun.com/storagetek/tape_storage/tape_libraries/sl8500/specs.xml. (eight) source: As of September three, 2008. IBM compares. The old DS8000 unlock supported "efficiency-optimized" fibre channel drives of seventy three, 146, and 300GB capacities. the brand new DS8000 R4 adds 450GB fibre channel drives. (9) source: http://www.technewsworld.com/story/64072.html?welcome=1218640804 (10) source: Underwood, Lee. "moving into on the 'cellular' web." Webreference.com. 8 Aug. 2008 http://www.webreference.com/programming/mobile/intro (eleven) supply: New IBM DR550 now has 1TB drives compared to outdated era of IBM DR550 which has 750GB drives, consequently expanding potential 33 %. (12) supply: Comparisons in accordance with published specifications, elements and advantages. evaluating the offering of the IBM DR550 vs. the EMC Centera primarily based on specs published at http://www.emc.com/products/aspect/hardware/centera.htm. (13) supply: effects from IBM TCO analyze for system Storage DR550, 2007. Cuts complete cost of possession by 50% with blended tape and disk offering. (14) source: As of September 3, 2008. Comparisons are in accordance with published statistics. The IBM TS1130 native sustained statistics rate (uncompressed) of one hundred sixty MBps http://www-03.ibm.com/methods/storage/tape/ts1130/requirements.html vs sun T10000 native sustained information fee (uncompressed) of one hundred twenty MBps http://www.sun.com/storagetek/tape_storage/tape_drives/t10000/specs.xml
The creation of the rising container of massive records brought with it the promise of extremely-scalable databases that might address terabytes of statistics at a time. As any one coping with gigantic datasets will attest to despite the fact, it gets impulsively complicated to with ease manipulate, save and retrieve suggestions in giant portions and how to examine if a cache is crucial.
If we’re to bring options valuable of the digital age, they need to be exploring new processes that surpass the current barriers in these days’s database technologies – congestion and scalability barriers that turn up both at the community and hardware levels function most important impediments to the administration and manipulation of massive facts units.
Why Use a Cache in big information functions?
The significance of a cache is self-evident: it reduces the strain on a database with the aid of positioning itself as an intermediary layer between the database and the conclusion users – more often than not, it'll switch records from a low-performance vicinity to a more robust-performance area (trust the change in getting access to statistics kept on a disk vs accessing the identical information in RAM). When a request is made, the returned information may also be stored in the cache in such a method that it may also be more with no trouble (and more swiftly) accessed sooner or later. a query will firstly are trying the cache, but when it misses, will fall returned on the database.
It makes much more feel for purposes that reuse the equal assistance again and again – suppose video game/message information, software rendering or scientific modelling. To take a simplified use case, believe a 3-tier app made of a presentation layer (the person interface), an application layer (dealing with the common sense for the app) and a data layer (the backend internet hosting the records).
These three layers may also be geographically separated, even though latency can be a limiting element because the three should invariably ‘communicate’ to every other. Let’s now assume that each and every particular person person in their app has a static records set that needs to be relayed to them each time they navigate to a brand new page – beginning on the statistics layer and ending on the presentation layer.
If the statistics layer is always queried, it ends up in excessive pressure and bad person journey brought about with the aid of latency. by way of introducing a cache, despite the fact, the records that's generally accessed can also be saved close by in brief memory, allowing it to be rapidly served to the presentation layer.
because of can charge and velocity considerations, a cache is just a little restricted within the measurement it may grow to. even so, the place effectivity is concerned, it's a imperative addition to any excessive-performance database provider.
From In-manner Caching to disbursed Caching
Many purposes use the mannequin described above for caching in the community – that's, a single illustration working alongside an utility. There are a few downsides to this approach, probably the most amazing being that it doesn’t scale very well for greater applications. On right of this, in the case of failure, states is generally irretrievable.
disbursed caching presents some improvements on this. because the name may additionally indicate, the cache is unfolded throughout a community of nodes in order no longer to rely on any single one to keep its state – proposing redundancy in the case of hardware failure or energy cuts and heading off the should commit local reminiscence to storing advice. on account that the cache now depends on a community of offsite nodes, though, it accrues technical fees the place latency is concerned.
distributed caching is advanced when it comes to scalability, and is frequently the model employed with the aid of business-grade items – with many, despite the fact, licensing fees and other charges frequently stand within the manner of actual scalability. in addition, there are sometimes trade-offs to be made – it’s elaborate to put into effect options which are both function-rich and excessive-performing.
It’s perhaps important to be aware, at this stage, that vertical scaling (upgrading the processing power of machines housing a big database) is not as good as horizontal scaling (where the identical database is break up up and distributed across situations) within the case of large statistics initiatives, as parallelization and speedy access to data are required.
constructing greater distributed Caches
in the digital age, it seems logical that dispensed caching would be more suitable suited to serve the needs of consumers looking for both safety and redundancy. Latency is at the moment an issue, but protocols comparable to sharding and swarming in the reduction of it significantly for well-related nodes.
chiefly, they should be able to convey flexible middleware options that permit industrial entities to join their databases to all the time-on-line networks of nodes, easing the burden placed on their backends and enabling them to enhanced serve end-clients with records. Scalability is most likely the most crucial consideration in building large data applications, and it’s time to begin proposing options that be certain it from the get-go.
in regards to the writer
Neeraj Murarka is an engineer and desktop programs architect with over 20 years event. he's the CTO and co-founder of Bluzelle, which is ushering in a decentralized information superhighway via it’s decentralized database protocol. He has worked for Google, IBM, Hewlett Packard, Lufthansa, Zynga, and Thales Avionics.
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Supercomputing | NewsIBM Launches 'Big Data' Bootcamps in Universities
Now that Watson has had its latest resurgence of fame and appeared as a top trending topic on both Google and Twitter, IBM is about to show college students how to use the underlying technologies of the supercomputer. In a push called "Big Data," the company will promote bootcamps on information management of massive amounts of data through university locations, IBM innovation centers, and online.
The camps, which are free, will last from three to five days and take place in classroom settings. Besides students, the company has invited IT professionals to participate. At the end of sessions, participants will have the chance to take free technical mastery tests and IBM certification exams.
Bootcamp sessions will cover discrete areas, including the use of IBM data management software such as DB2, pureXML, Informix, InfoSphere Optim and Guardium, and open source applications Hadoop and Eclipse. Students will receive lessons in management and analysis skills for big data environments, including data federation, integration, and warehousing techniques, as well as data management planning, and data governance, quality and security strategies.
The new initiative follows on IBM's Watson Jeopardy! victory, where the computer showed how artificial intelligence can work in the real world (at least in the real world of a game show). The system consists of 90 clustered IBM Power 750 Express servers, a potent build-up of hardware that can pick through 500 gigabytes of information a second.
But IBM said that as more organizations move to similar systems to handle their big data challenges, a skills gap is surfacing.
"Companies are amassing up to petabytes of information during peak hours of operations, and they see an opportunity to use this data to gain new insights into their customers and get ahead of the competition," said Arvind Krishna, general manager of IBM Information Management. "Uncovering insights hidden among data in existing IT systems, and outside of the firewall in social networks, on clouds, and from mobile devices, requires today's IT professionals to possess new skills."
Mahatma Gandhi Mission's College of Engineering & Technology in India recently launched campus workshops on DB2 for its engineering students and faculty. Currently, more than 600 students and faculty members are certified and trained on IBM technologies.
"IBM is bringing real world industry experience to students to keep them in touch with emerging technologies and IT trends such as big data," said Professor Nareshkumar Harale, head of Computer Engineering. "When universities and businesses collaborate, they build the next generation of skilled information technology leaders to create new opportunities, fuel economic growth and solve challenges that can improve the way they live."
Dian Schaffhauser is a senior contributing editor for 1105 Media's education publications THE Journal and Campus Technology. She can be reached at email@example.com or on Twitter @schaffhauser.
Posted by Fred Alcober and Sandeep Gupta, on behalf of the TensorFlow team
TensorFlow held its third and biggest yet annual Developer Summit in Sunnyvale, CA on March 6 and 7, 2019. The event was attended by approximately 1,000 machine learning enthusiasts and watched over livestream by tens of thousands more.
The event was comprised of two days filled with technical updates from the TensorFlow team and presentations from users showcasing amazing applications. They also held hacker-rooms, breakout sessions, and workshops. Attendees interacted with the TensorFlow team, got their questions answered, and collaborated with each other.
In the three years since launch, TensorFlow has matured into an entire end-to-end machine learning (ML) ecosystem, helping to power the ML revolution they see happening around us. It has been downloaded over 41 million times and has over 1,800 contributors from around the world. TensorFlow as a comprehensive ML platform is helping a diverse set of practitioners, researchers, and new users to build amazing new solutions to solve challenging problems with AI. For example:
At the developer summit, they announced the alpha release of TensorFlow 2.0, which marks the beginning of the TensorFlow 2.0 era and brings TensorFlow’s powerful capabilities to more developers and researchers, making it easier than ever to build and use ML. They also announced new community partnerships and education initiatives with O’Reilly Media, Udacity, Deeplearning.ai on Coursera, and fast.ai to help foster open source collaboration and train the next generation of new users. Further, they listened to their community and completely updated developer documentation and redesigned tensorflow.org to make it even easier to get access to resources and information.
Below are the highlights and key announcements from the event.Easy to use
In TensorFlow 2.0, the biggest focus has been on making the API simpler, more intuitive, and natural for all users. They are making the API components integrate better with tf.keras as the recommended high-level API for most users. This will enable developers to go from data ingestion, transformation, model building, training, and saving, to deployment much more easily. They launched TensorFlow Datasets, a collection of commonly used ML datasets prepared for easy use in TensorFlow.Developers in Rome new to ML are using TensorFlow to help paleographers decipher medieval manuscripts
Along with the TensorFlow 2.0 alpha release, they are providing conversion and migration tools and documentation to help with the transition from 1.x code to 2.0. These and many more resources, examples, and case-studies on TensorFlow can be accessed from the new tensorflow.org website.Power to experiment and invent
TensorFlow is accelerating state-of-the-art research. This begins with flexibility for researchers to prototype their ideas quickly, try many experiments, and iterate. With new features in TensorFlow 2.0 such as eager execution by default, intuitive Python control flows, automatic optimization of eager code with tf.function, and greatly improved error messaging, they are enhancing the researcher development experience.Researchers at NERSC at Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, and NVIDIA won the Gordon Bell Prize for successfully scaling a deep learning application on the Summit supercomputer using TensorFlow to study the effects of extreme weather
Large scale research in machine learning also requires massive parallel computing. Since last year, they have accelerated training on 8 V100s by more than 2x. Using a Cloud TPU v2, we’ve boosted performance by 1.6x, and with Intel MKL acceleration they have improved inference speed by more than 3 times. Getting great out of the box performance is a big focus of TensorFlow 2.0, and a core part of their progress towards final release.
The TensorFlow ecosystem includes a large collection of very powerful add-ons that expand TensorFlow in new and useful ways. Some of the add-ons that they described include:
TensorFlow Extended (TFX) brings the management of the entire machine learning lifecycle to their users. It has several component libraries and they announced new features in these components, but more significantly, the new orchestration support puts it all together to provide users with an integrated end-to-end platform (see example here). With support for your own orchestrator, the TFX components integrate with a metadata store. This store keeps track of all the component runs, the artifacts that went into them, and those that were produced. This enables advanced features like experiment tracking, model comparison, etc. that will greatly improve production use cases.TensorFlow for Mobile & IoT
TensorFlow Lite, their solution for running models on mobile and embedded systems, has exploded globally and is now running on more than 2 billion mobile devices — leading the next generation of ML on device. It’s helping users solve use cases like predictive text generation, image classification, object detection, audio recognition, text to speech and speech to text recognition, video segmentation, and edge detection among many others.
At the event, they heard how global internet companies such as Alibaba XianYuin and Netease are using TensorFlow Lite to provide users with better application experiences. They also talked about TensorFlow Lite’s incredible ML performance and how it’s powering ML in marquee Google applications such as Search, Assistant, Photos and Pixel.
We also shared their progress with the new Swift for TensorFlow package. With version 0.2 just released, users can see increased usability and try out this novel ML paradigm. To make it easier to get started with Swift, they launched a new machine learning course using Swift for TensorFlow by fast.ai.Commitment to community growth
The success of TensorFlow is in large part due to its amazing and growing community of users and developers. They have developed TensorFlow 2.0 in close engagement with the community, via an open RFC process, many new Special Interest Groups, and their Google Developer Expert community feedback and testing.
We have launched a new #PoweredByTF campaign and are discovering amazing new projects being built by their users. They announced the Google Summer of Code program where students can apply to come work with the TensorFlow engineering team for some hands-on development. They are also launching a new Powered by TF Challenge hosted on DevPost specifically for users to create and share their latest and greatest with TensorFlow 2.0.
Great educational resources are key to machine learning democratization and adoption. They announced two new educational resources to make it easier for beginners and learners to get started with TensorFlow. The first one is deeplearning.ai’s Course 1 — “Intro to TensorFlow for AI, ML and DL”, part of the TensorFlow: from Basics to Mastery series hosted on Coursera. The second one is Udacity’s Intro to TensorFlow for Deep Learning. Both courses are designed with developers in mind and require no prior machine learning experience and are available now.
And finally, they announced TensorFlow World, a new week-long conference dedicated to fostering open source collaboration and all things TensorFlow. This conference, co-presented by O’Reilly Media and TensorFlow, will be held in Santa Clara, CA on the week of October 28. Their vision is to bring together the amazing TensorFlow world and give an opportunity for folks to connect with each other. Call for proposals is open for attendees to submit interesting TensorFlow project papers or for companies to showcase their solutions using TensorFlow, and they can’t wait to see you there.
At Google, they believe AI research and applications will advance faster when all users have access to the best tools, allowing everyone to participate. TensorFlow is dedicated to helping empower all ML users. We’re committed to working with the community to make TensorFlow easy for everyone and to pursue AI for good!
As Europe looks to introduce its new General Data Protection Regulations (GDPR) in 2018, the arguments for and against more regulation continue to build.
Whether you are a customer or vendor though, the GDPR promise to unify — and therefore simplify — the compliance requirements for data protection is a positive.Are Regulations and Compliance Enough?
Of course, GDPR only applies to companies doing business within Europe, but it is a step in the right direction for the whole world. The current status quo leaves organizations to cobble together their own requirements, which for vendors and customers alike, are creating huge barriers to business innovation.
However, the trade-off between innovation from more sophisticated data analytics and the risk of litigation for non-compliance, remains ever-present. They all want the benefits that can accrue through appropriately targeted analytics, but at what cost?
The bigger question, though, is whether regulations and compliance can be enough to create the desired behaviors.Looking Through the Ethics Lens
At a recent conference on data privacy in Sydney, Australia, ethics expert and executive director of the Ethics Centre Simon Longstaff, noted, “When technical mastery is divorced from ethical intent, you get tyranny.”
Longstaff encouraged companies to apply their own ‘ethics lens’ when developing new applications that might put personal privacy at risk.Legal Compliance
At that same event, Data Governance Australia chairman Graeme Samuel suggested that legal compliance alone will not be sustainable in the long term, and that it will not only stifle innovation, but fail to deliver the best outcomes for consumers.
The unifying tenet of these arguments is that regulations will never keep up with the pace of technological development, so they need to look at other ways to govern the inappropriate use of personal data.
Perhaps that approach can be found in the market itself?Just Saying No to Privacy Concerns
A recent Australian national privacy survey indicated that around 60 percent of respondents choose not to deal with organizations that create privacy concerns for them. And these privacy concerns aren’t just related to unlawful activities.
For example, inside the enterprise, the idea of tracking ‘digital footprints’ is not new. Yet, although email archives are typically the legal property of the enterprise, most organizations will avoid applications that make their employees feel that their privacy is being compromised.Building Consumer Trust
Tech companies are also aware that their need to build trust with their customers goes way beyond their legal obligations. Google’s ‘Don’t be Evil’ code of conduct was an early acknowledgement of the potential power the company has over people’s lives.
On a smaller scale, when my company called itself SWOOP Analytics, one of their founders quickly identified the danger of that name being turned into ‘SNOOP Analytics’ instead.Looking Beyond Compliance
As the GDPR rolls out, many services are becoming available to help both vendors and clients comply with the new rules. But as I have highlighted, compliance is not the end game.
In fact, it would be naïve to think that the opportunity won’t still exist for behavior that technically complies with GDPR regulations but is still unethical. Therefore, GDPR advice needs to go beyond compliance to address more fundamental aspects of what constitutes ethical behavior.Scary Data Protection Risks
Nor is the line between ethical and non-ethical behavior black and white. In a recent discussion with a friend who sits on the boards of several publicly traded companies, she noted that they were continuously receiving presentations from IT security groups.
She reflected that the presenters did a great job of identifying data protection risks that could “scare the living daylights out of you.”The 5 Tenets of Risk Management 101
The dilemma, then, is getting the balance right. Beyond the given of legal compliance, it comes down to risk management 101:1. Identify the risks
For the consumers, enterprises and vendors alike, what are the worst things that could happen if personal data were to be lost? For example, someone finding out your gender might lead to some unwanted advertising. Losing access to financial information would, however, be potentially far more damaging.2. Determine your vulnerability to the identified risks
Inside the enterprise, individuals will be required to provide personal details to their employers. For example, employers will need your banking details to pay you. Understanding the potential vulnerabilities in your employer’s systems, as well as those of your bank, is very important.3. Assess the likelihood that these risks could materialize
Using the previous example, even if someone were to acquire your banking details, what is the likelihood that they would be able to do any material damage? Over time, consumers have become more relaxed about providing personal details on platforms like Facebook and LinkedIn as they start to assess their own cost/benefit trade-offs for doing so.4. Identify what actions you can take to mediate identified risks
Social platforms now provide you with many options to manage your personal exposure. Interestingly, fewer than 50 percent of us ever bother to use them.5. Prioritize and implement your risk mitigation actions
Whether you are an individual, vendor or enterprise, the best way to create the right balance for you between risk and reward will be to carefully prioritize your risk reduction strategies and tactics.
Laurence Lock Lee is the co-founder and chief scientist at Swoop Analytics, a firm specializing in online social networking analytics. He previously held senior positions in research, management and technology consulting at BHP Billiton, Computer Sciences Corporation and Optimice.
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