Archive for the ‘Artificial Intelligence’ Category

Dont forget to consider GDPR when using artificial intelligence in the workplace – ComputerWeekly.com

When applying for a new job, candidates may well find that the use of artificial intelligence (AI) tools is involved at some point in the recruitment process. New recruitment businesses and technology are entering the market, setting up entirely automated initial conversations with candidates to help them find the right vacancy for their skill set, saving time for applicant and recruiter alike.

CV screening is also becoming more prevalent, with AI screening and tracking tools being used to quickly analyse CVs to ascertain whether the individual has the qualifications and experience necessary for the role for example, burger chain Five Guys is said to be utilising such technology.

Unilever recently hit the headlines when it announced that, instead of human recruiters, it uses an AI system to analyse video interviews. Candidates record interviews on their phone or laptop, and the system scans candidates language, tone and facial expressions from the videos, assessing their performance against traits that are considered to indicate job success at Unilever.

But it is not just the recruitment stage where AI and people analytics are being used by businesses performance management is another targeted area. Amazon is leading this charge the company was issued with two patents in the US for a wristband for tracking the performance of workers in their warehouse, which would mean that staff receive a little buzz if they place a product near or in the wrong inventory location.

It is also alleged that Amazon uses a computer system to automatically generate warnings or terminations to employees, when their productivity (or lack of) warrants it.

The benefits of such technology for employers are countless and clear, including costs savings, efficiency, and the purported removal of human unconscious bias and prejudice. However, the use of AI in the workplace has come under scrutiny and has posed serious ethical and legal questions, including whether AI itself could in fact be biased.

Another important aspect when implementing AI in the workplace is its relationship with data protection laws such as the EUs General Data Protection Regulation (GDPR). So, what data protection considerations should an employer make when considering the introduction of AI technology?

The use of AI for processing personal data will usually meet the legal requirement for completing a DPIA.

A DPIA enables the business to analyse how the AI plans will affect individuals privacy, and ensures the company can assess the necessity and proportionality of its technology.

As the UK Information Commissioners guidance confirms, the deployment of an AI system to process personal data needs to be driven by the proven ability of that system to fulfil a specific and legitimate purpose, not just by the availability of the technology.

The DPIA should demonstrate that the applicable purposes the AI is being used for could not be accomplished in another reasonable way. In doing so, organisations need to think about and document any detriment to data subjects that could follow from bias or inaccuracy in the algorithms and data sets being used.

A business cannot simply process personal data because it wishes to do so data can only be processed where one of the legitimate grounds or conditions of processing has been met. There are various bases, including performance of a contract, compliance with a legal obligation, consent and legitimate business interests. For the processing of sensitive personal data (such as health data), the bases are even more limited.

Before using AI or people analytics in the workplace, employers will first need to consider what data is being processed by such activity and second what legal basis can be relied upon in processing the data in that way. If they do not have a legal basis, the data cannot be processed.

One of the key principles of GDPR is transparency, requiring businesses to provide individuals with mandatory information about the processing of their personal data, including the reason why it is being processed, the legal basis, who it will be shared with and how long it will be retained. Employers will need to update their privacy notices to ensure anyone subject to the AI technology is made aware of its use.

The privacy notice needs to be concise and intelligible, using clear and plain language this will be particularly difficult when including a complex AI system, as businesses will need to provide a meaningful explanation of the technology to meet the transparency principle of GDPR. Opaque or complex descriptions of the tech may result in contention or pushback from the employees and candidates affected.

GDPR prohibits instances of computer says no and contains the right for data subjects not to be subjected to a decision based solely on automated processing, which has a legal or similarly significant impact on them. Its aim is to protect individuals against the risk that a potentially damaging decision is taken without human intervention, and will therefore likely capture a recruitment result made without any human input.

There are specific exceptions when automated decision-making is permitted, including where explicit consent was given, contractual necessity, or where authorised by law. Where such an exception is being relied upon, such as with the consent of a candidate, the business must still implement further safeguarding measures, including permitting the individual to request human intervention or to contest the decision.

Employers will need to ensure that their automated technology is being lawfully used, before relying on its output.

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Dont forget to consider GDPR when using artificial intelligence in the workplace - ComputerWeekly.com

New research on adoption of Artificial intelligence within IoT ecosystem – ELE Times

element14, the Development Distributor, has published new research on the Internet of Things (IoT) which confirms strong adoption of Artificial Intelligence (AI) within IoT devices, alongside new insights on key markets, enablers and concerns for design engineers working in IoT.

AIoT is the major emerging trend from the survey, demonstrating the beginning of the process to build a true IoT ecosystem. Research showed that almost half (49%) of respondents already use AI in their IoT applications, with Machine Learning (ML) the most used technology (28%) followed by cloud-based AI (19%). This adoption of AI within IoT design is coupled with a growing confidence to take the lead on IoT development and an increasing number of respondents seeing themselves as innovators. However, it is still evident that some engineers (51%) are hesitant to adopt AI due to being new to the technology or because they require specialized expertise in how to implement AI in IoT applications.

Other results from element14s second Global IoT Survey show that security continues to be the biggest concern designers consider in IoT implementation. Although 40% cited security as their biggest concern in 2018 and this has reduced to 35% in 2019, it is still ranked significantly higher than connectivity and interoperability due to the type of data collected from things (machines) and humans, which can be very sensitive and personal. Businesses initiating new IoT projects treat IoT security as a top priority by implementing hardware and software security to protect for any kind of potential threat. Ownership of collected data is another important aspect of security, with 70% of respondents preferring to own the data collected by an edge device as opposed to it being owned by the IoT solution provider.

The survey also shows that although many engineers (46%) still prefer to design a complete edge-to-cloud and security solution themselves, openness to integrate production ready solutions, such as SmartEdge Agile, SmartEdge IIoT Gateway, which offer a complete end-to-end IoT Solution, has increased. 12% more respondents confirmed that they would consider third party devices in 2019 than 2018, particularly if in-house expertise is limited or time to market is critical.

A key trend from last years survey results has continued in 2019 and survey results suggest that the growing range of hardware available to support IoT development continues to present new opportunities. More respondents than ever are seeing innovation coming from start-ups (33%, up from 26%), who benefit from the wide availability of modular solutions and single board

computers available on the market. The number of respondents adopting off-the-shelf hardware has also increased to 54% from 50% in 2018.

Cliff Ortmeyer, Global Head of Technical Marketing for Farnell and element14 says: Opportunities within the Internet of Things and AI continue to grow, fueled by access to an increasing number of hardware and software solutions which enable developers to bring products to market more quickly than ever before, and without the need for specialized expertise. This is opening up IoT to new entrants, and giving more developers the opportunity to innovate to improve lives. element14 provides access to an extensive range of development tools for IoT and AI which provide off-the shelf solutions to common challenges.

Despite the swift integration of smart devices such as Amazons Alexa and Google Home into daily life, evidencing a widespread adoption of IoT in the consumer space, in 2019 we saw a slight shift in focus away from home automation with the number of respondents who considered it to be the most impactful application in IoT in the next 5 years reducing from 27% to 22%. Industrial automation and smart cities both gained, at 22% and 16% respectively, underpinned by a growing understanding of the value that IoT data can bring to operations (rising from 44% in 2018 to 50% in 2019). This trend is witnessed in industry where more manufacturing facilities are converting to full or semi-automation in robotic manufacturing and increasing investment in predictive maintenance to reduce production down times.

The survey was conducted between September and December 2019 with 2,015 respondents participating from 67 countries in Europe, North America and APAC. Responses were predominantly from engineers working on IoT solutions (59%), as well as buyers of components related to IoT solutions, Hobbyists and Makers.

element14 provides a broad range of products and support materials to assist developers designing IoT solutions and integrating Artificial Intelligence. Products are available from leading manufacturers such as Raspberry Pi, Arduino and Beagleboard. element14s IoT hub and AI pages also provide access to the latest products for development and insights and white papers to support the design journey. Readers can view an infographic covering the full results of the element14 Global IoT Survey at Farnell in EMEA, Newark in North America and element14 in APAC.

For more information, visit http://www.element14.com

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New research on adoption of Artificial intelligence within IoT ecosystem - ELE Times

SparkCognition Named to the 2020 CB Insights AI 100 List of Most Innovative Artificial Intelligence Startups – Star Local Media

AUSTIN, Texas, March 4, 2020 /PRNewswire/ --CB Insights today named SparkCognition to the fourth annual AI 100 ranking, showcasing the 100 most promising private artificial intelligence companies in the world. This makes SparkCognition one of only two companies to be listed on every AI 100 List since its inauguration in 2017.

"It's been remarkable to see the success of the companies named to the Artificial Intelligence 100 over the last four years. The 2019 AI 100 saw 48 companies go on to raise $4.9B of additional financing and nine got acquired," said CB Insights CEO Anand Sanwal. "It has been gratifying to see that CB Insights' data-driven approach to identifying the top AI companies using patents, customer traction, investor quality, market sizing and more has become so effective at picking the AI winners of tomorrow. We look forward to seeing what the 2020 AI 100 companies will accomplish over the course of this year and beyond."

In addition to disrupting core sectors including healthcare, retail, and finance, the 2020 AI 100 companies are revamping the broader enterprise tech stack. These companies span the globe, from the US, UK, China, Chile, and South Africa, and are supported by more than 600 investors.

"We're very happy to be named to CB Insights' AI 100 List for the fourth time," said Amir Husain, Founder and CEO of SparkCognition. "2019 was a banner year with tremendous value delivery to our clients, a $100M funding round, significant product releases, and seminal advancements in our AI research. And we are poised for an even more fantastic 2020!"

Through an evidence-based approach, the CB Insights research team selected the AI 100 from nearly 5,000 companies based on several factors including patent activity, investor quality, news sentiment analysis, proprietary Mosaic scores, market potential, partnerships, competitive landscape, team strength, and tech novelty. The Mosaic Score, based on CB Insights' algorithm, measures the overall health and growth potential of private companies to help predict a company's momentum.

SparkCognition is a leading industrial artificial intelligence company that builds AI solutions for industrial applications, working with industries including energy, aerospace and aviation, cybersecurity, and more. With a foundation of deep AI expertise and investment in research and advancing the science of artificial intelligence, SparkCognition currently offers four main products: SparkPredict, an analytics solution, Darwin, a data science automation platform, DeepArmor, a cybersecurity platform, and DeepNLP, a natural language processing solution. In October 2019, SparkCognition announced the close of its $100M Series C funding round from investors including March Capital Partners, Temasek, Kerogen Digital Solutions, and Hearst Ventures.

Quick facts on the 2020 AI 100:

About CB InsightsCB Insights helps the world's leading companies accelerate their digital strategy and transformation efforts with data, not opinion. Our Emerging Tech Insights Platform provides companies with actionable insights and tools to discover and manage their response to emerging technology and startups. To learn more, please visit http://www.cbinsights.com.

Contact:CB Insightsawards@cbinsights.com

About SparkCognition:

With award-winning machine learning technology, a multinational footprint, and expert teams focused on defense, IIoT, and finance, SparkCognition builds artificial intelligence systems to advance the most important interests of society. Our customers are trusted with protecting and advancing lives, infrastructure, and financial systems across the globe. They turn to SparkCognition to help them analyze complex data, empower decision-making, and transform human and industrial productivity. SparkCognition offers four main products:DarwinTM, DeepArmor, SparkPredict, and DeepNLPTM. With our leading-edge artificial intelligence platforms, our clients can adapt to a rapidly changing digital landscape and accelerate their business strategies. Learn more about SparkCognition's AI applications and why we've been featured in CNBC's 2017 Disruptor 50, and recognized three years in a row on CB Insights AI 100, by visiting http://www.sparkcognition.com.

Contact:Cara SchwartzkopfSparkCognitioncschwartzkopf@sparkcognition.com512-956-5491

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SparkCognition Named to the 2020 CB Insights AI 100 List of Most Innovative Artificial Intelligence Startups - Star Local Media

Iktos and SRI International Announce Collaboration to Combine Artificial Intelligence and Novel Automated Discovery Platform for Accelerated…

- Researchers will utilize Iktos generative modeling AI technology with SRIs SynFini synthetic chemistry platform to discover new compounds against multiple viruses, including the Wuhan coronavirus (COVID-19) -

Iktos, a company specialized in artificial intelligence (AI) for novel drug design and SRI International (SRI), a research center headquartered in Menlo Park, California, today announced that the companies have entered into a collaboration agreement designed to accelerate discovery and development of novel anti-viral therapies. Under the collaboration, Iktos generative modeling technology will be combined with SRIs SynFini, a fully automated end-to-end synthetic chemistry system, to design novel, optimized compounds and accelerate the identification of drug candidates to treat multiple viruses, including influenza and the Wuhan coronavirus (COVID-19).

Iktos AI technology, based on deep generative models, helps bring speed and efficiency to the drug discovery process by automatically designing virtual novel molecules that have all of the desirable characteristics of a novel drug candidate. This tackles one of the key challenges in drug design: rapid and iterative identification of molecules which simultaneously validate multiple bioactive attributes and drug-like criteria for clinical testing.

"Iktos generative AI technology has proven its value and potential to accelerate drug discovery programs in multiple collaborations with renowned pharmaceutical companies. We are eager to apply it to SRIs endonuclease program, and hope our collaboration with SRI can make a difference and speed up the identification of promising new therapeutic option for the treatment of COVID-19," said Yann Gaston-Math, co-founder and CEO of Iktos. "We are excited at the prospect of combining our automated compound design technology with SRIs SynFini platform and the potential this has to further accelerate drug discovery."

SRIs SynFini platform is designed to accelerate chemical discovery and development, and thereby bring new drugs to the clinic more quickly and affordably. The closed loop SynFini platform automates the design, reaction screening and optimization (RSO), and production of target molecules. SynFini comprises three components that work seamlessly together: a software platform (SynRoute), a reaction screening platform (SynJet), and a multi-step flow chemistry automation and development platform (AutoSyn).

SRI has an ongoing program focused on discovering drugs to block endonuclease enzymes that are common to many viruses. These enzymes are involved in viral replication and blocking of host resistance to infection. Sequence analysis of COVID-19 indicates that this virus has an endonuclease that it is genetically about 97 percent similar to the SARS virus. Recent studies show that blocking the SARS virus endonuclease inhibits the infections pathogenesis, leading to a 100 percent survival rate in preclinical models. This suggests that the COVID-19 endonuclease is a good therapeutic target.

"The SynFini system has the potential to dramatically expedite small molecule drug discovery," said Nathan Collins, Ph.D., Chief Strategy Officer of SRIs Biosciences Division and Head of the SynFini program. "We look forward to exploring how the integration of Iktos AI-driven generative molecule combined with SynFini supports the rapid and efficient discovery of new drugs to treat emerging infectious diseases."

By combining platforms for the accelerated molecular design and automated production of target molecules with established high-throughput biology, Iktos and SRI hope to demonstrate a new paradigm in extremely rapid drug discovery against high-value pharmaceutical targets.

About Iktos

Incorporated in October 2016, Iktos is a French start-up company specialized in the development of artificial intelligence solutions applied to chemical research, more specifically medicinal chemistry and new drug design. Iktos is developing a proprietary and innovative solution based on deep learning generative models, which enables, using existing data, to design molecules that are optimized in silico to meet all the success criteria of a small molecule discovery project. The use of Iktos technology enables major productivity gains in upstream pharmaceutical R&D. Iktos offers its technology both as professional services and as a SaaS software platform, Makya. Iktos is also developing Spaya, a synthesis planning software based upon Iktoss proprietary AI technology for retrosynthesis.

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About SRI International

SRI International, a non-profit research institute founded in 1946 and headquartered in Menlo Park, California, creates world-changing solutions to make people safer, healthier, and more productive. SRI Biosciences, a division of SRI International, integrates basic biomedical research with drug and diagnostics discovery, and preclinical and clinical development. SRI Biosciences has produced several marketed drugs and advanced more than 100 drugs to clinical trials. The division is focused on novel platforms and programs in a variety of therapeutic areas targeting high unmet medical needs. SRI Biosciences collaborates with a broad range of partners from small and virtual biotechnology companies to top 10 pharmaceutical companies and other leading industry partners. More information is available at http://www.sri.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20200303005770/en/

Contacts

For Iktos Yann Gaston-Math, CEOcontact@iktos.com +33 6 30 07 99 26

For SRI Melissa Wagner, Business Developmentmelissa.wagner@sri.com +1 650 859 3505

Michele Parisi, Mediamparisi@forwardhealthinc.com +1 925 864 5028

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Iktos and SRI International Announce Collaboration to Combine Artificial Intelligence and Novel Automated Discovery Platform for Accelerated...

Why we need to adapt existing EU laws to Artificial Intelligence – European Public Health Alliance

By Louise Lamatsch, Policy Assistant, EPHA

Artificial Intelligence (AI) and other emerging digital technologies have the potential to build up public health capacity to deliver equitable solutions by improving screening, diagnosis, and treatments across many medical disciplines. In addition, AI can generate productivity gains and improve operational efficiency by providing more precise and complete information, better workflow management and refine continuity of care. However, these technologies are still in their infancy. Their increased use within society and the healthcare sector require sufficient safeguards and guidelines to minimize the risk of harm these technologies may cause to individuals.

Future research will need to set the focus even more on the vulnerability and liability gaps in AI as well as on the adjustments that need to be made in the already existing EU legislation, such as the Product Liability Directive. Concerning already existing liability regimes regarding digital technologies, the law of tort of EU Member states is largely non- harmonised, except for the Product Liability Law under Directive 85/374/ EC, liability for infringing Data Protection Law under Article 82 of the General Data Protection Regulation (GDPR) and liability for infringing Competition Law under the directive 2014/ 104/ EU. Thus on National level, it can be observed that laws of the Member States do not contain liability rules specifically applicable to damage resulting from the use of emerging digital technologies such as Artificial Intelligence. Adequate and complete liability regimes in the development of technological challenges are crucially important for society to ensure that damage or harm caused by emerging digital technologies do not lead to victims ending up totally or partially uncompensated.

As discussed at the recent workshop on Civil Liability Regime for Artificial Intelligence in the European Parliament, organized by the S&D group and hosted by MEP Tiemo Wlken (Germany), the following key suggestions (among many others) could be included in future discussions and research regarding the adjustments that need to be made on existing EU liability regimes:

AI is a difficult and complex system, which needs better understanding, building up health literacy, and research. Most importantly, the existing liability laws do not necessarily have to be reinvented but they will require modification and adjustment. . The EU should, therefore, try to find a balanced solution based on a harmonized and human-centred approach on AI to ensure civil protection and a fair and safe environment. In the health sector existing laws should be specifically adapted in the field of health and safety at workplace. AI may not only affect the employment area and wages but also the way workers approach their work and this could have an impact on their well-being such as job satisfaction, stress and health in a variety of ways. AI is therefore not only related to potential physical harm but also mental harm. The integration of Big Data and AI technologies into health systems must be accompanied by appropriate legislation, rules and standards that protect the fundamental rights of individuals and address new ethical challenges. Emerging technologies is an area, which still needs much discussion and research before we have a well-performing digital and AI- friendly European Union.

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Why we need to adapt existing EU laws to Artificial Intelligence - European Public Health Alliance