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December 2021. GOTHENBERG.

We speak to Jesper Ekberg from the Swedish Association of Local Authorities and Regions (SALAR), and Region Jönköping County in Sweden.

As we prepare for the International Forum, which takes place in Gothenburg on 20-22 June 2022 (postponed from March 2022), Jesper Ekberg speaks to us about creating fairer systems to tackle the inequalities in health.



"My heart is really beating a lot around quality improvement and how that can come closer to the public health area".


Jesper will be involved in three sessions at the conference.




Podcast release: December 2021


Find out more about the International Forum Gothenburg 2022: internationalforum.bmj.com/gothenburg/


May 24, 2022. INDIA.

The overall Indian public cloud services market is expected to reach $13.5 billion by 2026, growing at a CAGR of 24% for 2021-26.

The Indian public cloud services (PCS) market, including infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS) solutions, and software-as-a-service (SaaS), revenue totaled $4.6 Billion for 2021, according to the International Data Corporation (IDC) Worldwide Semi-annual Public Cloud Services Tracker, 2H21 (July-December). The overall Indian public cloud services market is expected to reach $13.5 billion by 2026, growing at a CAGR of 24% for 2021-26.


"With digital innovation leading the top business objectives for Indian organizations, cloud adoption is set to accelerate in 2022. Driven by the need for agility, flexibility, and faster access to digital technologies, cloud continues to gain momentum across segments. Additionally, the need to leverage data intelligently, is supreme and enterprises are able to do so with access to technologies that are built on a cloud foundation," says Rishu Sharma, Associate Research Director, Cloud and Artificial Intelligence, IDC India.


SaaS continued to be the largest component of the overall public cloud services market, followed by IaaS and PaaS in 2021. Public cloud spending continued to increase among enterprises, with the top two service providers holding more than 45% of the Indian public cloud services market.


India continues to be among the fastest-growing market for public cloud service providers due to the robust demand from large enterprises, digital natives, and also from small and medium businesses in the country. In 2021, enterprises continued to invest in public cloud to ensure business continuity, improve resilience and productivity, and drive digital innovation.


There has been an increased demand for cloud-based security applications as organizations expect part of their hybrid workforce to return to offices in 2022. Apart from migrating existing workloads to the public cloud, there is also an increased demand for cloud-native application development after the pandemic, driven by the need to bring ideas faster to the market and address customer demands.


"Public cloud adoption continued to surge in 2021 as enterprises invested in public cloud as part of their digital transformation initiatives to improve business resiliency and become a digital-first organization. The increased spend is expected to continue in the upcoming years as enterprises invest in emerging technologies like AI/ML, IoT, blockchain, etc., to automate processes and drive innovation with public cloud as the foundation. The increasing investments in areas like edge computing and IoT will drive the demand for public cloud infrastructure services, especially storage and data management," says Harish Krishnakumar, Senior Market Analyst, IDC India.


—Ends—


For more information about IDC's tracker products and research services, please contact Shivani Anand, Senior Marketing Specialist at sanand@idc.com . You can also follow IDC India’s Twitter and LinkedIn pages for regular updates.


About IDC Trackers

IDC Tracker products provide accurate and timely market size, company share, and forecasts for hundreds of technology markets from more than 100 countries around the globe. Using proprietary tools and research processes, IDC's Trackers are updated on a semiannual, quarterly, and monthly basis. Tracker results are delivered to clients in user-friendly excel deliverables and on-line query tools. The IDC Tracker Charts app allows users to view data charts from the most recent IDC Tracker products on their iPhone and iPad.


About IDC

International Data Corporation (IDC) is the premier global provider of market intelligence, advisory services, and events for the information technology, telecommunications, and consumer technology markets. With more than 1,200 analysts worldwide, IDC offers global, regional, and local expertise on technology, IT benchmarking and sourcing, and industry opportunities and trends in over 110 countries. IDC’s analysis and insight helps IT professionals, business executives, and the investment community to make fact-based technology decisions and to achieve their key business objectives. Founded in 1964, IDC is a wholly owned subsidiary of International Data Group (IDG), the world’s leading tech media, data, and marketing services company. To learn more about IDC, please visit www.idc.com. Follow IDC on Twitter at @IDC and LinkedIn. Subscribe to the IDC Blog for industry news and insight

How well do IBM, Microsoft, and Face++ AI services guess the gender of a face? The Gender Shades project evaluates the accuracy of AI powered gender classification products.

This evaluation focuses on gender classification as a motivating example to show the need for increased transparency in the performance of any AI products and services that focused on human subjects. Bias in this context is defined as having practical differences in gender classification error rates between groups.


1270 images were chosen to create a benchmark for this gender classification performance test.


The subjects were selected from 3 African countries and 3 European countries. The subjects were then grouped by gender, skin type, and the intersection of gender and skin type.


Gender Labels

Gender was broken into female and male categories since evaluated products provide binary sex labels for the gender classification feature. The evaluation inherits these sex labels and this reduced view of gender which is a more complex construct.


The dermatologist approved Fitzpatrick skin type classification system was used to label faces as Fitzpatrick Types I, II, III, IV, V, or VI.


Then faces labeled Fitzpatrick Types I, II, and III were grouped in a lighter category and faces labeled Fitzpatrick Types IV, V, and VI were grouped into a darker category.


Three companies - IBM, Microsoft, and Face++ - that offer gender classification products were chosen for this evaluation based on geographic location and their use of artificial intelligence for computer vision.


While the companies appear to have relatively high accuracy overall,there are notable differences in the error rates between different groups. Let's explore.


All companies perform better on males than females with an 8.1% - 20.6% difference in error rates.


All companies perform better on lighter subjects as a whole than on darker subjects as a whole with an 11.8% - 19.2% difference in error rates.


When we analyze the results by intersectional subgroups - darker males, darker females, lighter males, lighter females - we see that all companies perform worst on darker females.IBM and Microsoft perform best on lighter males. Face++ performs best on darker males.


IBM and Microsoft perform best on lighter males. Face++ performs best on darker males.


IBM had the largest gap in accuracy, with a difference of 34.4% in error rate between lighter males and darker females.


IBM Watson leaders responded within a day after receiving the performance results and are reportedly making changes to the Watson Visual Recognition API. Official Statement.


Error analysis reveals 93.6% of faces misgendered by Microsoft were those of darker subjects.


An internal evaluation of the Azure Face API is reportedly being conducted by Microsoft. Official Statement. Statement to Lead Researcher.


Error analysis reveals 95.9% of the faces misgendered by Face++ were those of female subjects.


Face++ has yet to respond to the research results which were sent to all companies on Dec 22 ,2017


At the time of evaluation , none of the companies tested reported how well their computer vision products perform across gender, skin type, ethnicity, age or other attributes.


Inclusive product testing and reporting are necessary if the industry is to create systems that work well for all of humanity. However, accuracy is not the only issue. Flawless facial analysis technology can be abused in the hands of authoritarian governments, personal adversaries, and predatory companies. Ongoing oversight and context limitations are needed.


While this study focused on gender classification, the machine learning techniques used to determine gender are also broadly applied to many other areas of facial analysis and automation. Face recognition technology that has not been publicly tested for demographic accuracy is increasingly used by law enforcement and at airports. AI fueled automation now helps determine who is fired, hired, promoted, granted a loan or insurance, and even how long someone spends in prison.


For interested readers, authors Cathy O'Neil and Virginia Eubanks explore the real-world impact of algorithmic bias.


Automated systems are not inherently neutral. They reflect the priorities, preferences, and prejudices - the coded gaze - of those who have the power to mold artificial intelligence.


We risk losing the gains made with the civil rights movement and women's movement under the false assumption of machine neutrality. We must demand increased transparency and accountability.


Learn more about the coded gaze -algorithmic bias - at www.ajlunited.org

Dive Deeper:

Test Inclusively:



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