Archive for July, 2021

"Promising development in the fight with cancer using artificial intelligence" with a new privacy-preserving approach named MEDomics -…

"We reported results of the first longitudinal approach to natural language processing of unstructured medical notes and demonstrate its ability to update and improve a prognostic model over time, as a patient's oncologic illness course unfolds," said Olivier Morin, leader of the project and head of the physics division at UCSF. The work was pioneered at UCSF, and is the result of a collaboration among an international consortium comprising U.S., (UCSF, San Francisco) Canadian (McGill, Universit de Sherbrooke, Montreal) and European centers (Oncoray in Dresden and Maastricht University).

Catherine Park, M.D. Co-senior author and Chair of the department of Radiation Oncology at UCSF added: "With this data we were able to validate findings of published clinical trials using real world data, e.g. the positive impact of immunotherapy in lung cancer. In addition, there are exciting opportunities to generate hypothesis based on associations from patients' individual health profiles, and risk factors."

Professor Phillippe Lambin senior author and Chair of the department of Precision Medicine at Maastricht University adds, "The MEDomics infrastructure allowed us to validate several new clinical hypotheses like the importance of cardio-vascular morbidity for the outcome of cancer treatment."

The consortium has created a secure, dynamic, continuously learning and expandable infrastructure, termed MEDomics, designed to constantly capture multimodal electronic health information, including imaging, across a large and multicentric healthcare system (watch the animation: https://youtu.be/2030Pdgm3_4).

Dr. Morin and collaborators added, now part of the code is open source and we would like to expand the international consortium (visitwww.medomics.ai).Our vision is to create an open-source computation platform integrating all MEDomics developments and from which both clinical staff and research scientists could tackle a diverse range of oncological problems using AI.

Contact: Dr. Olivier Morin PhD, [emailprotected], +14153089257

SOURCE University of California - San Francisco

ucsf.edu

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"Promising development in the fight with cancer using artificial intelligence" with a new privacy-preserving approach named MEDomics -...

Research shows AI is often biased. Here’s how to make algorithms work for all of us – World Economic Forum

Can you imagine a just and equitable world where everyone, regardless of age, gender or class, has access to excellent healthcare, nutritious food and other basic human needs? Are data-driven technologies such as artificial intelligence and data science capable of achieving this or will the bias that already drives real-world outcomes eventually overtake the digital world, too?

Bias represents injustice against a person or a group. A lot of existing human bias can be transferred to machines because technologies are not neutral; they are only as good, or bad, as the people who develop them. To explain how bias can lead to prejudices, injustices and inequality in corporate organizations around the world, I will highlight two real-world examples where bias in artificial intelligence was identified and the ethical risk mitigated.

In 2014, a team of software engineers at Amazon were building a program to review the resumes of job applicants. Unfortunately, in 2015 they realized that the system discriminated against women for technical roles. Amazon recruiters did not use the software to evaluate candidates because of these discrimination and fairness issues. Meanwhile in 2019, San Francisco legislators voted against the use of facial recognition, believing they were prone to errors when used on people with dark skin or women.

The National Institute of Standards and Technology (NIST) conducted research that evaluated facial-recognition algorithms from around 100 developers from 189 organizations, including Toshiba, Intel and Microsoft. Speaking about the alarming conclusions, one of the authors, Patrick Grother, says: "While it is usually incorrect to make statements across algorithms, we found empirical evidence for the existence of demographic differentials in the majority of the algorithms we studied.

Ridding AI and machine learning of bias involves taking their many uses into consideration

Image: British Medical Journal

To list some of the source of fairness and non-discrimination risks in the use of artificial intelligence, these include: implicit bias, sampling bias, temporal bias, over-fitting to training data, and edge cases and outliers.

Implicit bias is discrimination or prejudice against a person or group that is unconscious to the person with the bias. It is dangerous because the person is unaware of the bias whether it be on grounds of gender, race, disability, sexuality or class.

This is a statistical problem where random data selected from the population do not reflect the distribution of the population. The sample data may be skewed towards some subset of the group.

This is based on our perception of time. We can build a machine-learning model that works well at this time, but fails in the future because we didn't factor in possible future changes when building the model.

This happens when the AI model can accurately predict values from the training dataset but cannot predict new data accurately. The model adheres too much to the training dataset and does not generalize to a larger population.

These are data outside the boundaries of the training dataset. Outliers are data points outside the normal distribution of the data. Errors and noise are classified as edge cases: Errors are missing or incorrect values in the dataset; noise is data that negatively impacts on the machine learning process.

Analytical techniques require meticulous assessment of the training data for sampling bias and unequal representations of groups in the training data. You can investigate the source and characteristics of the dataset. Check the data for balance. For instance, is one gender or race represented more than the other? Is the size of the data large enough for training? Are some groups ignored?

A recent study on mortgage loans revealed that the predictive models used for granting or rejecting loans are not accurate for minorities. Scott Nelson, a researcher at the University of Chicago, and Laura Blattner, a Stanford University economist, found out that the reason for the variance between mortgage approval for majority and minority group is because low-income and minority groups have less data documented in their credit histories. Without strong analytical study of the data, the cause of the bias will be undetected and unknown.

What if the environment you trained the data is not suitable for a wider population? Expose your model to varying environments and contexts for new insights. You want to be sure that your model can generalize to a wider set of scenarios.

A review of a healthcare-based risk prediction algorithm that was used on about 200 million American citizens showed racial bias. The algorithm predicts patients that should be given extra medical care. It was found out that the system favoured white patients over black patients. The problem with the algorithms development is that it wasn't properly tested with all major races before deployment.

Inclusive design emphasizes inclusion in the design process. The AI product should be designed with consideration for diverse groups such as gender, race, class, and culture. Foreseeability is about predicting the impact the AI system will have right now and over time.

Recent research published by the Journal of the American Medical Association (JAMA) reviewed more than 70 academic publications based on the diagnostic prowess of doctors against digital doppelgangers across several areas of clinical medicine. A lot of the data used in training the algorithms came from only three states: Massachusetts, California and New York. Will the algorithm generalize well to a wider population?

A lot of researchers are worried about algorithms for skin-cancer detection. Most of them do not perform well in detecting skin cancer for darker skin because they were trained primarily on light-skinned individuals. The developers of the skin-cancer detection model didn't apply principles of inclusive design in the development of their models.

Testing is an important part of building a new product or service. User testing in this case refers to getting representatives from the diverse groups that will be using your AI product to test it before it is released.

This is a method of performing strategic analysis of external environments. It is an acronym for social (i.e. societal attitudes, culture and demographics), technological, economic (ie interest, growth and inflation rate), environmental, political and values. Performing a STEEPV analysis will help you detect fairness and non-discrimination risks in practice.

The COVID-19 pandemic and recent social and political unrest have created a profound sense of urgency for companies to actively work to tackle inequity.

The Forum's work on Diversity, Equality, Inclusion and Social Justice is driven by the New Economy and Society Platform, which is focused on building prosperous, inclusive and just economies and societies. In addition to its work on economic growth, revival and transformation, work, wages and job creation, and education, skills and learning, the Platform takes an integrated and holistic approach to diversity, equity, inclusion and social justice, and aims to tackle exclusion, bias and discrimination related to race, gender, ability, sexual orientation and all other forms of human diversity.

The Platform produces data, standards and insights, such as the Global Gender Gap Report and the Diversity, Equity and Inclusion 4.0 Toolkit, and drives or supports action initiatives, such as Partnering for Racial Justice in Business, The Valuable 500 Closing the Disability Inclusion Gap, Hardwiring Gender Parity in the Future of Work, Closing the Gender Gap Country Accelerators, the Partnership for Global LGBTI Equality, the Community of Chief Diversity and Inclusion Officers and the Global Future Council on Equity and Social Justice.

It is very easy for the existing bias in our society to be transferred to algorithms. We see discrimination against race and gender easily perpetrated in machine learning. There is an urgent need for corporate organizations to be more proactive in ensuring fairness and non-discrimination as they leverage AI to improve productivity and performance. One possible solution is by having an AI ethicist in your development team to detect and mitigate ethical risks early in your project before investing lots of time and money.

The views expressed in this article are those of the author alone and not the World Economic Forum.

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Research shows AI is often biased. Here's how to make algorithms work for all of us - World Economic Forum

The Global Artificial Intelligence Market is expected to grow by $ 13.26 billion during 2021-2025, progressing at a CAGR of almost 47% during the…

Global Artificial Intelligence Market in the Industrial Sector 2021-2025 The analyst has been monitoring the artificial intelligence market in the industrial sector and it is poised to grow by $ 13.

New York, July 22, 2021 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence Market in the Industrial Sector 2021-2025" - https://www.reportlinker.com/p04647367/?utm_source=GNW 26 billion during 2021-2025, progressing at a CAGR of almost 47% during the forecast period. Our report on the artificial intelligence market in the industrial sector provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors.The report offers an up-to-date analysis regarding the current global market scenario, latest trends and drivers, and the overall market environment. The market is driven by an increase in the adoption of data-guided decision making and evolving industrial IoT and big data integration. In addition, an increase in the adoption of data-guided decision making is anticipated to boost the growth of the market as well.The artificial intelligence market in the industrial sector analysis includes the end-user segment and geographic landscape.

The artificial intelligence market in the industrial sector is segmented as below:By End-user Process industries Discrete industries

By Geography North America Europe APAC MEA South America

This study identifies the rise in demand for cloud-based AI solutionsas one of the prime reasons driving the artificial intelligence market in the industrial sector growth during the next few years.

The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters. Our report on artificial intelligence market in the industrial sector covers the following areas: Artificial intelligence market in the industrial sector sizing Artificial intelligence market in the industrial sector forecast Artificial intelligence market in the industrial sector industry analysis

This robust vendor analysis is designed to help clients improve their market position, and in line with this, this report provides a detailed analysis of several leading artificial intelligence market vendors in the industrial sector that include Alphabet Inc., Amazon.com Inc., General Electric Co., International Business Machines Corp., Intel Corp., Landing AI, Microsoft Corp., Oracle Corp., SAP SE, and Siemens AG. Also, the artificial intelligence market in the industrial sector analysis report includes information on upcoming trends and challenges that will influence market growth. This is to help companies strategize and leverage all forthcoming growth opportunities.The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to an analysis of the key vendors.

The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters such as profit, pricing, competition, and promotions. It presents various market facets by identifying the key industry influencers. The data presented is comprehensive, reliable, and a result of extensive research - both primary and secondary. Technavios market research reports provide a complete competitive landscape and an in-depth vendor selection methodology and analysis using qualitative and quantitative research to forecast the accurate market growth.Read the full report: https://www.reportlinker.com/p04647367/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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The Global Artificial Intelligence Market is expected to grow by $ 13.26 billion during 2021-2025, progressing at a CAGR of almost 47% during the...

Artificial intelligence and warfare – an introduction (podcast) – Shephard News

Introducing Shephard Studios Artificial Intelligence on the Battlefield podcast, sponsored by our partner Systel.

Welcome to the first episode of theArtificial Intelligence on the Battlefield podcast. Listen onApple Podcasts,Google Podcasts,Spotify and more.

Artificial Intelligence (AI) is no longer the stuff of science fiction but part of everyday reality.

The promise and massive advantages of AI have led to doctrinal shifts and reimagining of systems and approaches for militaries around the world.

AI can now be found in a vast range of military technology, from autonomous systems to data-gathering sensors.

AI and machine learning applications are much quicker than humans, reducing user workload and enhancing productivity. This poses significant challenges and opportunities for militaries.

Welcome to Shephard Studios Artificial Intelligence on the Battlefield podcast, sponsored by our partner Systel.

Over the course of three episodes, we are looking at the evolution of AI and machine learning in modern warfare.

We discuss the changing capabilities of the US and its allies, as well as the growing challenge from their peer competitors.

And well consider areas such as information processing and human-machine teaming, asking what this will mean for warfighters in the coming decades.

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Artificial intelligence and warfare - an introduction (podcast) - Shephard News

Mini trade war imminent? EU rejects the UK’s attempts to overhaul the Brexit deal – CNBC

LONDON, ENGLAND - JUNE 09: Cabinet Minister Lord Frost (R) chairs the first meeting of the Partnership Council followed by the eighth meeting of the withdrawal agreement joint committee with his EU counterpart Maros Sefcovic (L), Richard Szostak, Principal Adviser, Service for the EU-UK Agreements (2ndL) and Paymaster General, Penny Mordaunt (2ndR), on June 9, 2021 in London, England.

Eddie Mulholland - WPA Pool/Getty Images

The European Union rejected a call from the British government to overhaul the Northern Ireland Protocol, a key tenet of the agreement that saw the U.K. leave the EU in 2020.

U.K. Brexit Minister David Frost and Secretary of State for Northern Ireland Brandon Lewis on Wednesday set out a "command paper" urging European leaders to renegotiate the protocol, on the basis that it has turned out to be unworkable in practice.

"We are ready to continue to seek creative solutions, within the framework of the Protocol, in the interest of all communities in Northern Ireland," the European Commission said in a statement late on Wednesday. "However, we will not agree to a renegotiation of the Protocol."

The deal was negotiated and signed by the British government in 2019 and ratified by the British Parliament, but the government is now seeking to renege on its commitments due to the challenges arising from its implementation.

The protocol, in principle, helps prevent customs checks and an effective land border between Northern Ireland, which is part of the U.K., and the Republic of Ireland, which remains in the EU.

BELFAST, NORTHERN IRELAND - APRIL 07: Nationalists and Loyalists riot against one another at the Peace Wall interface gates which divide the two communities on April 7, 2021 in Belfast, Northern Ireland.

Charles McQuillan/Getty Images

However, it has led to port inspections on goods traveling between Great Britain and Northern Ireland, a development that has angered businesses and drawn criticism for effectively creating a border in the Irish Sea. This has stoked historical sectarian tensions in Northern Ireland.

Secretary of State for Business, Energy and Industrial Strategy Kwasi Kwarteng told Sky News on Thursday that "nobody could guarantee the effects of the Northern Ireland Protocol until we left the EU."

Kwarteng also claimed the agreement wasn't "written in stone," despite it being written into international law.

Christopher Granville, managing director for EMEA and global political research at TS Lombard, told CNBC Thursday that the process of kicking the can down the road on Northern Ireland has already begun, with a three-month extension in place until September of a grace period on food and other products being transported between Great Britain and Northern Ireland.

The British government said in its command paper that it believes the current situation satisfies the criteria for invoking Article 16 of the Protocol, which allows for its suspension in the case of "serious economic difficulties." However, it has expressed reluctance to trigger this clause just yet. The EU, Granville said, will take the position that a party cannot claim "serious difficulties" before the full terms of the agreement have been implemented.

A lorry passes through security at the Port of Larne in Co Antrim, Northern Ireland on December 6, 2020.

PAUL FAITH | AFP | Getty Images

"These positions point to the following kind of negotiation: the EU rejects the U.K. proposal for an 'honesty box' approach to goods shipments from GB to NI; but the EU will propose fast-track regulatory checks on shipments of foodstuffs arriving in NI from GB with additional facilitations for trusted traders," Granville explained.

"To the extent that such negotiations produce any agreements, both sides will be able to claim victory: the UK will say that it has renegotiated the Protocol, the EU will say that it has found the best way to implement the Protocol."

However, he noted that such agreements will be difficult to establish, and there will be "cliff-hangers" as the grace periods approach their expiry date and the parties come out with the "usual threats" of withdrawal and litigation.

While these disputes grab the headlines, Granville said the crucial reality unfolding beneath the surface will be a fundamental shift in supply chains.

"Essentially these will shift from east-west (i.e. GB-NI) to north-south (i.e. ROI-NI, with ROI in this context meaning both Ireland in its own right and as a channel for shipment from all of the rest of the EU)," he explained.

LONDON - Brexit minister Lord Frost making a statement to members of the House of Lords in London on the government's approach to the Northern Ireland Protocol.

House of Lords/PA Images via Getty Images

"This adjustment will mean over time (even in time for Christmas) that there will be no empty shelves in NI supermarkets on the basis of which U.K. politicians could invoke the 'serious economic difficulties' criterion of Article 16."

British businesses such as Marks & Spencer that are facing delays in fresh produce delivery from Great Britain to Northern Ireland would then have to either expand their supply chains within the Republic of Ireland, Granville suggested, or leave their Northern Irish market share to be taken up by a company operating in the Republic or the broader EU.

James Smith, developed markets economist at ING, said there are two possible ways the renewed stand-off could affect the British economy.

"A positive though seemingly unlikely outcome is that the UK government opts to align more closely to EU food standards after all, removing barriers not only for GB-NI trade, but also on exports to the EU," he told CNBC on Thursday.

"But with trust between both sides clearly low, the bigger near-term question is whether further legal steps are taken by Brussels that eventually culminate in tariffs and in a negative scenario, some form of mini trade war."

Although things may not get that far in reality, Smith said, such a scenario would reintroduce disruption to U.K. exports which have partially recovered from the sharp decline in January, after the U.K.'s formal separation from the bloc.

BELFAST, Northern Ireland: A Loyalist holds a placard with words 'Stormont Or The Protocol?' during a protest against the Northern Ireland Protocol at the entrance to Belfast Harbour.

Artur Widak/NurPhoto via Getty Images

"At a bigger macro level however, the effects of Covid-19 are still likely to dominate the outlook over coming months, with the impact of Brexit likely to have a less noticeable impact on GDP in the short-term," Smith added.

TS Lombard's Granville suggested that the main opposition Labour party in the U.K. may push for the "easy and instant solution" of aligning with the EU's food standards, which Prime Minister Boris Johnson's pro-Brexit Conservative government will be reluctant to do as it undermines the "sovereignty" at the core of its electoral platform.

He anticipates that if the process of kicking the can down the road lasts until the Northern Irish elections next May, and present polling remains consistent, pro-Irish republican party Sinn Fein will emerge as the largest single party in the devolved Northern Irish Assembly.

"I haven't yet got a clear view for now on exactly how this might change the political dynamic over the Protocol dispute, but it will surely do so," Granville said.

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Mini trade war imminent? EU rejects the UK's attempts to overhaul the Brexit deal - CNBC