During armed conflict, unequal power relations and structural disadvantages derived from gender dynamics are exacerbated. There has been increased recognition of these dynamics during the last several decades, particularly in the context of sexual and gender-based violence in conflict, as exemplified for example in United Nations Security Council Resolution 1325 on Women, Peace, and Security. Though initiatives like this resolution are a positive advancement towards the recognition of discrimination against women and structural disadvantages that they suffer from during armed conflict, other aspects of armed conflict, including, notably, the use of artificial intelligence (AI) for targeting purposes, have remained resistant to insights related to gender. This is particularly problematic in the operational aspect of international humanitarian law (IHL), which contains rules on targeting in armed conflict.
The Gender Dimensions of Distinction and Proportionality
Some gendered dimensions of the application of IHL have long been recognized, especially in the context of rape and other categories of sexual violence against women occurring during armed conflict. Therefore, a great deal of attention has been paid in relation to ensuring accountability for crimes of sexual violence during times of armed conflict, while other aspects of conflict, such as the operational aspect of IHL, have remained overlooked.
In applying the principle of distinction, which requires distinguishing civilians from combatants (only the latter of which may be the target of a lawful attack), gendered assumptions of who is a threat have often played an important role. In modern warfare, often characterized by asymmetry and urban conflict and where combatants can blend in with the civilian population, some militaries and armed groups have struggled to reliably distinguish civilians. Due to gendered stereotypes of expected behavior of women and men, gender has operated as a de facto “qualified identity that supplements the category of civilian.” In practice this can mean that, for women to be targeted, IHL requirements are rigorously applied. Yet, in the case of young civilian males, the bar seems to be lower – gender considerations, coupled with other factors such as geographical location, expose them to a greater risk of being targeted.
An illustrative example of this application of the principle of distinction is in so-called “signature strikes,” a subset of drone strikes adopted by the United States outside what it considers to be “areas of active hostilities.” Signature strikes target persons who are not on traditional battlefields without individually identifying them, but rather based only on patterns of life. According to reports on these strikes, it is sufficient that the persons targeted “fit into the category ‘military-aged males’, who live in regions where terrorists operate, and ‘whose behavior is assessed to be similar enough to those of terrorists to mark them for death.’” However, as the organization Article 36 notes, due to the lack of transparency around the use of armed drones in signature strikes, it is difficult to determine in more detail what standards are used by the U.S. government to classify certain individuals as legal targets. According to a New York Times report from May 2012, in counting casualties from armed drone strikes, the U.S. government reportedly recorded “all military-age males in a strike zone as combatants […] unless there is explicit intelligence posthumously proving them innocent.”
Continue reading: https://www.justsecurity.org/77970/embedding-gender-in-international-humanitarian-law-is-artificial-intelligence-up-to-the-task/

Women vis-à-vis Technology: Negotiating the Challenge of Disengagement
What is the position and status of women vis-à-vis technology in general and new technology in particular? The vital but sensitive question demands closer scrutiny.  Studies have found that in terms of enlistment in various courses and classes relating to cutting-edge technology or in terms of employment in high-tech firms, the percentage of women is very low. In fact, it is considered quite impressive if women come to constitute only one-fourth of the total number. If that is not enough, it is also a fact that women earn much less than their male counterparts. This scenario holds true despite a substantial increase in the enrolment of women in schools and higher academic institutions.
A persistent trend that one finds is that much fewer numbers of women opt for the STEM disciplines in their pre-professional days. This is one though not the only cause of the reflection of lesser women in a workforce involved in scientific, industrial, and technological fields. A world in which half of the human population is supposed to be women is a major cause for concern. It does not augur well when the amazing progress in technology takes place without much involvement of women. The following points expose some of the daily challenges experienced by women in technology to climb up the success ladder:
Unequal Opportunities: The mindset of society is still engaged with gender bias across the world, even in the 21st century. The tech world is known as the male-dominated profession because it is an unconscious bias that women are inferior and cannot understand technical issues or possess better technical skills than men. Thus, women in technology receive fewer work opportunities and promotions due to inequality.
Maternal Leave: The tech-driven world still considers women as child-bearing machines who cannot work due to household chores and child management. Women in the technology field lack that confidence because they know maternal leave can hamper their job opportunities and may not be encouraged to join an office after completing maternal leave. Women have to hold back from successful careers and focus on motherhood due to lack of sufficient support— mental and physical.
Discriminations at Every Stage: Receiving constant insults in a work environment creates a negative impact on the women in the technology field— being talked over, being ignored, giving more opportunities to men-counterpart, being left out of group events, and the list goes on. If any woman stands up for herself and her rights, she is considered to be bold and male employees view her negatively. Women have to continuously fight for their rights and stand up against these daily insults at every stage possible.
Continue reading: https://www.analyticsinsight.net/the-10-most-impactful-women-in-technology-2021/

Every new technology brings with it questions of ethics and unintended consequences. It’s right to ask these questions, but it’s also important to remember that humans are completely at the helm with how these technologies are implemented and when and where they are restrained.
Humanity is deeply ingrained in their success and failure. Looking closely, we can see technologies reflect humanity’s imperfections back to us. But I contend technologies like artificial intelligence can enhance, rather than reduce, the human experience.
Much has been made of digital echo chambers over the years, and in many cases, digital platforms have become dehumanizing. The platforms are not communities; they are launching points, and that’s largely because humans at the helm took it too far or chose not to use the technologies available. This is all part of our digital evolution.
The answer is adding humanity back into the digital world. What does this mean? In simplest terms, it’s remembering why and who the tech was envisioned for in the first place. It’s about striking balance.
Imagine a global digital community built to reflect the actual world around us, a diverse, globally attainable community. AI technology could build balanced, vibrant inclusive communities. When people see community moderation that rewards celebration and respect, then they themselves will become more conditioned to behave accordingly within the community. And when the community is a safe place, there’s room for creativity and expression, which is the essence of what it means to be human.
With AI, the digital age can complement humanity like never before. No doubt the training of AI for this application will go through some learning phases, but this application builds bridges and creates opportunities for authentic connections.
Continue reading: https://thenextweb.com/news/ai-can-enhance-real-virtual-lives-syndication

This article was written by Micaela Kaplan, Ethics in AI Lead, CallMiner
Artificial intelligence (AI) and machine learning (ML) have become ubiquitous in our everyday lives. From self-driving cars to our social media feeds, AI has helped our world operate faster than it ever has, and that’s a good thing — for the most part.
As these technologies integrate into our everyday lives, so too have the many questions around the ethics of using and creating these technologies. AI tools are models and algorithms that have been built on real-world data, so they reflect real-world injustices like racism, misogyny, and homophobia, along with many others. This data leads to models that perpetuate existing stereotypes, reinforce the subordination of certain groups of people to the majority population, or unfairly delegate resources or access to services. All these outcomes cause major repercussions for both consumers and businesses alike.
While many companies have begun recognizing these potential problems in their AI solutions, only a few have begun building the structures and policies to address them. The fact is that AI and social justice can no longer operate as two separate worlds. They need the influence of each other to create tools that will help us build the world we want to see. Addressing the ethical questions surrounding AI and understanding our social responsibilities is a complicated process that involves the challenging work and dedication of many people. Below are a few actionable things to keep in mind as you begin the journey towards responsible AI.
Create a space that allows people to voice their questions and concerns
When studying ethics in any capacity, facing uncomfortable truths comes with the territory. The strongest teams in the fight for responsible AI are those that are honest with themselves. These teams acknowledge the biases that appear in their data, their models, and themselves. They also consider how these biases affect the world around them. Noticing and acting on the biases and impacts requires honest group discussion.
Dedicating the time and space to have these conversations is critical in ensuring that these conversations can be just that — conversations. As teams, we need to create spaces that allow us to speak freely on topics that might be controversial without fear of consequences. This fundamentally requires the support of executives. Sometimes, it might be easier to have a team meet and discuss without executives and then present the group’s ideas to the executives later. This level of anonymity can help provide a sense of security, because ideas presented on behalf of the team cannot be traced back to a single person. Allowing for open communication and honest feedback is what allows us to confront these questions productively. In the fight for ethical AI, it’s not a team against each other; it’s the team against the potential problems in the model.
Continue reading: https://venturebeat.com/2021/08/28/4-considerations-when-taking-responsibility-for-responsible-ai/

Considering the numerous benefits that Artificial Intelligence brings in, almost all the organizations across the globe have been relying on this magnificent technology to get their objectives accomplished and goals met. To reap the best benefits out of AI, firms must make a solid case around how AI will deliver. On that note, here are a few tips and recommendations that the firms can employ to make the case and/or strengthen your business case for Artificial Intelligence and build support.
Providing examples of real-life success stories
Nothing can be more motivating than real-life success stories. This, when incorporated while making the case for AI would turn out to be a huge success. Including early success stories from the pilot projects within the organization is a great way to start with.
Create excitement 
One of the most important points to note is that Artificial Intelligence is constantly changing. Thus, encouraging the team members to talk about the same among themselves develops excitement thereby naturally building the momentum. Also, this is an excellent way to ensure that the gap between strategy and execution is reduced to a large extent.
Get the senior executives into action
What many tend to not take into account how important the role of senior executives is when it comes to building a strong business case for AI. When senior executives work with the AI teams to ensure that the AI system’s input and output will be aligned with their overall digital transformation strategy, the results obtained are exceptional. Well, not just that. The collaborative strategy sessions help in bringing broader visibility to AI initiatives and keep AI research and development efforts tethered to key needs of the business.
Look beyond ROI
It is now high time that we look at Artificial Intelligence as merely a way to capture new revenue. Giving importance to how AI is a roadmap to a plethora of opportunities is needed at this point.
Portraying AI as an epitome of innovation
Today, AI stands the potential for the business leaders to encourage engagement from all levels of the organization than merely being treated as something that operates behind the scenes. Possibly every innovation that one can think of has some relation or the other with the magical world of Artificial Intelligence.
AI as a digital transformation strategy
Going a step further, AI has been easier than ever as far as digitalisation, be it in the form of digital operations or delivering digital services for that matter is concerned. The digital experience that one gets to take full advantage of by virtue of AI surely deserves appreciation.
Integrating AI teams
Asking an AI team to work in a small silo is probably one of the most common mistakes observed. What could be a way out then? Well, integrating the AI teams into the organization would fetch results that surpass the expectations.
Continue reading: https://www.analyticsinsight.net/how-to-strengthen-business-case-for-artificial-intelligence-and-build-support/

The use of artificial intelligence has increased productivity and efficiency in the workplace in nearly every industry. As such, a number of companies have turned to AI to improve their recruiting process—a task that once required hours of sorting through resumes, calling applicants and scheduling interviews to find the perfect candidate.
Despite these advancements, not all companies are aware of the massive benefits that a more automated recruiting process can offer. Below, a panel of Forbes Coaches Council members share ways AI can improve recruiting and the overall hiring process.
1. It Streamlines The Recruiting Process
AI can make recruiting a seamless, smooth action. It can expedite the recruiters’ communications through automated interview confirmation emails, so they have time to actually build relationships with the candidates. This can help them save time and fill positions more quickly. It can also screen and rank candidates faster as well as decrease bias, though it really depends on how it has been programmed and by whom. - Sahar Andrade, MB.BCh, Sahar Consulting, LLC
2. It Can Screen For Suitable Talents
AI can especially help when HR is screening applicants for suitable talents on social media, such as on LinkedIn, for example. Since AI-based screening is algorithm-driven and easy to repeat, this means recruiters’ added value for companies and job seekers lies less in their keyword searches and more in their ability to confirm talents offline. - Michael Thiemann, Strategy-Lab™
3. It Can Remove Unconscious Bias
Artificial intelligence, if set up correctly, can remove unconscious bias caused by names, locations, university names, photos and more by removing these discriminating factors from search criteria and the reviewing process up front. This would make hiring a more equal, less time-consuming process. But the emphasis has to be placed on setting the inclusion and exclusion criteria up fairly. - Victoria Canham, Ahead Together Ltd
Continue reading: https://www.forbes.com/sites/forbescoachescouncil/2021/08/27/key-ways-artificial-intelligence-can-improve-recruiting-in-the-hiring-process/?sh=3346a6d82c52

Artificial intelligence (AI) is not new, but it is revolutionizing the world. Paired with emerging technologies, the applications for AI currently appear to be endless. From accelerating the pace of life saving drugs to streamline operations for cost-savings and revenue amplification, AI platforms are omnipresent, and their impact is inescapable.
IBM terms it the “innovation equation,” and explains that AI became the world’s fastest-growing tech tool for one reason: necessity. The digital age ushered in previously unthinkable quantities of data. Since almost every system in the world relies on, uses, or generates data, something faster than the human mind was needed to organize it. 
Enter AI. Now, you would be hard-pressed to find a company or platform that doesn’t use AI in some way. AI-built, AI-fueled, AI-powered, AI-informed: it is pervasive. In the hands of innovators, the disruption of AI of companies worldwide trends in a positive direction, and has the potential to change the world. In this article we’ll dive into 15 of the most innovative companies in AI right now and the seismic shifts they are causing across industries.
Abacus AI
In the past decade, deep learning neural networks have been used for tasks such as image recognition and speech understanding. The idea is that an artificial neural network can be trained to perform a task by showing it many examples of inputs and desired outputs (examples are called training data). These networks can also be designed so that they recognize patterns or structures in input data by using unsupervised learning algorithms.
Founded by Bindu Reddy, Arvind Sundararajan and Venkat (Siddartha) Naidu, Abacus.AI is the world’s first end-to-end AI and ML platform. Abacus.AI has developed several deep-learning techniques and their expert AI system can be used to train custom neural networks based on the use-case and datasets.
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Organizations can use these techniques to train models or bring their own ML and DL models and use their state-of-the-art toolset that allows data science teams to wrangle data, build real-time machine and deep learning features, upload ipython notebooks, monitor model drift and set up CI/CD for machine learning systems. Their one of kind real-time deep learning platforms makes it extremely simple to launch and monitor personalization, time-series, anomaly detection and NLP models with ease. 
Data Prophet
In the early 1960s, General Motors was one of the first manufacturers to implement a production line with AI. Some benefits for factory owners when implementing an intelligent system are improved quality and increase in throughput/production output while reducing costs or lead time to market by using some examples like robotic process automation (RPA), smart sensors, machine learning (ML) predictive analytics and natural language processing (NLP). 
DataProphet is an award-winning, VC-funded, high-growth AI-as-a-Service company that enables manufacturers to step towards autonomous manufacturing. Co-founded by Frans Cronje in 2014, the DataProphet team are innovators of a novel deep learning technology which harnesses prescriptive analytics for proactive, continual optimization of manufacturing systems. 
Continue reading: https://www.forbes.com/sites/anniebrown/2021/08/27/15-innovative-ai-companies-driving-exponential-shifts-in-their-respective-sectors/?sh=5994674c2bc0

Women in the AI field are making research breakthroughs, spearheading vital ethical discussions, and inspiring the next generation of AI professionals. We created the VentureBeat Women in AI Awards to emphasize the importance of their voices, work, and experience and to shine a light on some of these leaders. In this series, publishing Fridays, we’re diving deeper into conversations with this year’s winners, whom we honored recently at Transform 2021. Check out last week’s interview with a winner of our AI rising star award.
No one got more nominations for a VentureBeat AI award this year than Katia Walsh, a reflection of her career-long effort to mentor women in AI and data science across the globe.
For example, Mark Minevich, chair of AI Policy at International Research Center of AI under UNESCO, said, “Katia is an impressive, values-driven leader [who has] been a diversity champion and mentor of women, LGBTQ, and youth at Levi Strauss & Co, Vodafone, Prudential, Fidelity, Forrester, and in academia over many years.” And Inna Saboshchuk, a current colleague of Walsh’s at Levi Strauss & Co, said, “a single conversation with her will show you how much she cares for the people around her, especially young professionals within AI.”
In particular, these nominators and many others highlighted Walsh’s efforts to upskill team members. Most recently, she launched a machine learning bootcamp that allowed people with no prior experience to not only learn the skills, but apply them every day in their current roles.
VentureBeat is thrilled to present Walsh with this much-deserved AI mentorship award. We recently caught up with her to learn more about the early success of her latest bootcamp, the power of everyday mentorship, and the role it can play in humanizing AI.
This interview has been edited for brevity and clarity.
VentureBeat: You received a ton of nominations for this award, so clearly you’re making a real impact. How would you describe your approach to AI mentorship?
Katia Walsh: My approach is not specific to AI mentorship, but rather overall leadership. I consider myself to be a servant leader, and I see my job as serving the people on my teams, my partners’ teams, and at the companies that I have the privilege to work for. My job is to remove barriers to help them grow, learn, engage, and mobilize others to succeed. So that extends to AI, but it’s not limited to that alone.
VentureBeat: Can you tell us about some of the specific initiatives you’ve launched? I know at Levi Strauss & Co, for example, you recently created a machine learning bootcamp to train more than 100 employees who had no prior machine learning experience, most of them women. That’s amazing. 
Walsh: Absolutely. So we are still in the process. We just started our first cohort between April and May, where we took people with absolutely no experience in coding or statistics from all areas of the company — including warehouses, distribution centers, and retail stores — and sought to make sure we gave people across geographies and across the company the opportunity to learn machine learning and practice that in their day job, regardless of what that day job was.
So we trained the first cohort with 43 people, 63% of whom were women in 14 different locations around the world. And that’s very important because diversity comes in so many different ways, including cultural and geographic diversity. And so that was very successful; every single one of those employees completed the bootcamp. And now we’re about to start our second cohort with 60 people, which will start in September and complete in November.
VentureBeat: I’m glad you mentioned those different aspects of diversity, because the industry is full of conversations around diversity, inclusion efforts, and ethical AI — some of them more genuine than others. So how does AI mentorship ladder up to all that?
Walsh: I see it as just yet another platform to make an impact. AI is such an exciting field, but it can also be seen as intimidating. Some people don’t know if it’s technology or business, but the answer is both. In fact, AI is actually part of our personal lives as well. One of my goals is to humanize the field of AI so that everyone understands the benefits and feels the freedom and the power to contribute to it. And by feeling that, they will in turn help make it even more diverse. At the end of the day — at this point, at least — AI is the product of human beings, with all of human beings’ mindsets, capabilities, and limitations. And so, it’s also imperative to ensure that when we create algorithms, use data, and deliver digital products, we do our very best to really reflect the world we live in.
Continue reading: https://venturebeat.com/2021/08/27/how-to-upskill-your-team-to-tackle-ai-and-machine-learning/

Companies like C3.ai and Palantir have shown that selling AI technology can be quite lucrative. After all, these companies command significant market caps and are growing quickly.
Yet selling AI technology remains difficult. Customers often want customized solutions that are based on their unique data sets. There are also the issues of adoption. The fact is that many AI projects fail to go beyond the proof-of-concept phase.
Then what are some ways to sell AI technologies? Let’s take a look:
It’s Not About Platforms: Many AI vendors extol their “platforms” that can seemingly solve any problems. But this approach is usually off the mark. Let’s face it, there are already top platforms that have solid features and powerful ecosystems.
“Businesses should sell a solution to a problem,” said Muddu Sudhakar, who is the CEO and founder of Aisera. “Customers will buy a platform when multiple solutions are acquired and there are the right integrations. Customers don't have free money sitting on the side just to invest in platforms.”
Sudhakar believes that an AI solution needs to show value within three to six months and there must be a return on investment within the first year.
Insights: It is often fuzzy as to what an AI system does. But for businesses, one of the most compelling aspects of this technology is about getting insights on tough questions. 
Take the example of eightfold.ai. Founded in 2016, the company is focused on leveraging AI for the talent management category.
“A lot of the problems that organizations are looking to solve are intimidating because they don't always have a clear answer,” said Kamal Ahluwalia, who is the President of Eightfold.ai. “There's no one second solution to 'why can't I hire the right people' or 'what skills do I need to be teaching my team so we're ahead of the game in a few years?' But the data is there, and it's usually just not being looked at correctly, or it's not feasible to do so for thousands or millions of times over. AI is all about applying that data, at scale.”
Continue reading: https://www.forbes.com/sites/tomtaulli/2021/08/27/how-to-sell-ai/?sh=24808b363177

Precision agriculture helps boost a farmer’s bottom line and keeps workers safe, but it could also be a key driver in solving the global food crisis.
Precision agriculture gives farmers the tools, data, and resources they need to make critical decisions about their crops. And even though one of the significant advantages of tech-aided farming is cost savings, there’s much more to it than boosting a farmer’s bottom line.
For example, farmers worldwide are using Precision Ag to address the global hunger crisis. By streamlining farming processes and reducing food waste, precision agriculture will likely become a considerable component of agricultural operations in the future.
Solving global hunger and reducing food waste are two significant areas where precision farming can help.
What Is Precision Agriculture?
Precision agriculture aims to increase crop yields and profits by measuring and analyzing critical data points using the latest and greatest tools and technology. Farmers use helpful devices like drones, in-ground sensors, and even farm robots to revolutionize farming and keep workers safe.
As with many other industries, making data-driven decisions is quickly becoming the norm in planting, monitoring, protecting, and harvesting crops.
What are the types of Precision Agriculture?
Examples of precision agriculture (commonly called precision ag) include:

• Measuring soil levels
• Pest and insect monitoring
• Seed and pesticide distribution
• Hydration monitoring and application
• Predictive seed planting analysis
• Optimum crop harvesting time

What are the benefits of Precision Agriculture?
Precision agriculture aims to increase a farmer’s bottom line and give them access to the best data possible. But the benefits of precision ag go further than that.
Other advantages include:

• Farmers can reduce pesticides by applying them to targeted areas instead of mass-distribution
• Cost savings on fuel and fertilizer
• Safer working conditions for employees
• Less food waste and more efficient crop yields (which could help combat global food insecurity)

How Can Precision Agriculture help with global food insecurity?
Global food insecurity exists even in established countries. Six hundred ninety million people worldwide (according to the United Nations) suffer from hunger and malnourishment. Twenty-two percent of children younger than five are developmentally stunted due to malnourishment and underfeeding (according to Our World In Data).
Continue reading: https://iotbusinessnews.com/2021/08/27/46936-precision-agriculture-is-helping-to-solve-global-food-insecurity-heres-how/

A research hub is looking at AI (Artificial Intelligence), drones and big data, alongside other new-age, to help the UAE achieve its national food security vision.
The Sharjah Research Technology and Innovation Park (SRTI Park) has been researching innovative technologies such as hydroponics and aquaponics and using seawater to grow food as it seeks to help the country and the region achieve food security.
"We have been harnessing technology for agricultural production and food security," said Hussain Al Mahmoudi, CEO of SRTI Park. "We have developed hydroponics, and also have a 150-square-metre aquaponics farm (combination of raising fish and cultivating plants in tanks) called Merlin Agrotunnel, that can produce over one tonne of organic vegetables and fruit every month."
Al Mahmoudi said the SRTI Park is a hub for researchers, entrepreneurs, start-ups and industry experts who develop solutions that can shape food production, not only in the UAE but also regionally and globally.
"Research and further development of farming methods agricultural technology will definitely accelerate the sector's growth. We can also use AI and big data to boost agricultural production. We can use drones to map out plants suitable on outdoor farms to save resources," he continued.
Talking about hydroponics, Al Mahmoudi said: "It involves a rather large cost in the beginning, but it significantly reduces the consumption of water – by about 70 per cent – and uses less or no fertilisers, which makes it perfect to grow food in a desert environment with less agricultural space and far less water resources."
Aquaponics, he explained, is a form of agriculture that combines raising fish in tanks with soilless plant culture (hydroponics). The nutrient-rich water from raising fish provides a natural fertiliser for the plants, and the plants help to purify the water for the fish.
Indoor farming, Al Mahmoudi said, eliminates extreme outdoor temperatures and makes particular sense in our desert environment. "We use very little water – about 90 per cent less than conventional farming – and because it is aquaponics, we also produce fresh fish along with a range of vegetables and fruits."
The water used to irrigate the fruit and vegetables is seawater, desalinated through solar energy, thus completing the development of an integrated system ensuring the sustainability of natural resources.
Sustainable food in a land-scarce environment
Al Mahmoudi said a team of botanists, agriculturists and engineers from Merlin International has been conducting research to develop soil-free vertical cultivation (farming) technology that is the ideal way to produce sustainable food in a land-scarce environment.
"This agricultural system at SRTI Park is one of the solutions to the problems of agriculture and food production. The agrotunnel can be combined into multiple units to create a commercial farm to provide fresh organic produce for multiple households daily," he said.
Continue reading: https://www.khaleejtimes.com/news/sharjah-drones-hydroponics-to-boost-uae-food-security

OneSky announced its part of a collaborative effort implementing the world’s first nationwide voluntary Network Remote Identification (NET-RID) program in Switzerland.
Swiss U-Space (SUSI) is a public-private partnership between the Swiss Federal Office of Civil Aviation (FOCA), the Swiss ANSP Skyguide and commercial stakeholders in drones and unmanned traffic management. The NET-RID project demonstrates a remote ID system that balances the needs of law enforcement and federal agencies for security with the needs of the aviation community for safety. The SUSI cooperative system of NET-RID provides insight into air traffic across an entire country – insight that can help aviators adjust flight plans as necessary to improve safety and optimize operations.
Based in Exton, Pennsylvania OneSky is an unmanned aircraft system traffic management ( UTM ) company developing airspace assessment, operations and management solutions for the aviation industry. The company develops web and mobile displays for the public and government to have better situational awareness of the unmanned air picture.
Remote ID (RID) technology is intended to remove the anonymity of the operator, much like a car’s license plate identifies the driver. This is done with electronic systems for aircraft because license plates and tail numbers aren’t visible from the ground and can add to a drone’s load capacity. RID solves the anonymity issue by attaching an electronic tag to a drone operation. This electronic tag is anonymous to the public but linked to a drone registration database where personal information is stored about the drone owner or operator. The Swiss FOCA has developed a drone operator registry, through which drone operators can share their information and get a unique identification number.
Remote ID can be accomplished by two different recognized methods. The first method is using a networked computer system that receives telemetry from a drone via a ground control station (GCS) or potentially attached hardware capable of sending updates through cellular networks (Network-RID, or NET-RID). The second method uses a broadcast device to push telemetry and the drone tag over a direct RF link to a smartphone (Broadcast-RID). In the SUSI NET-RID program, identification information is shared through the interoperable, open-source InterUSS Platform: allowing U-Space Service Providers (USSP) to exchange information as needed.
Continue reading: https://insideunmannedsystems.com/switzerland-implements-nationwide-rid-service-for-drones-with-onesky/

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Market Analysis by Applications: Physical Business & E-commerce
Worldwide Internet Of Things In Retail Quantitative Market Data
Market Data breakdown by major geographies, Type & Application/End-users • Worldwide Internet Of Things In Retail Market Revenue & Growth Rate by Type [, Internet Of Things In Retail markets by type, Beacons, RFID Tags, Sensors, Wearables & Others] (2016-2026) • Worldwide Internet Of Things In Retail Market Revenue & Growth Rate by Application [Physical Business & E-commerce] (2016-2026) • Worldwide Internet Of Things In Retail Market Revenue & Growth Rate by Each Region Specified (2016-2026) • Worldwide Internet Of Things In Retail Market Volume & Growth Rate by Each Region Specified, Application & Type (2016-2026) • Worldwide Internet Of Things In Retail Market Revenue Share & Y-O-Y Growth Rate by Players (2020)
Important Features that are under offering & key highlights of the Worldwide Internet Of Things In Retail market report: 1. Why lots of Key players are not profiled in Study? –> The market study is surveyed collecting data of various companies from Worldwide Internet Of Things In Retail industry, and the base for coverage is NAICS standards. However, the study is not limited to profile only few companies; connect with sales executive to get customized list. The standard version of research report is listed with players like IBM Corporation, Impinj, Allerin Tech Pvt & RetailNext
2. Does Scope of Market Study allow further Segmentation? —> Yes, for a deep dive analysis add-on segmentation is applicable in premium customized version of report to better derive market values. The standard version of this report covers segmentation by Application [Physical Business & E-commerce], by Type [, Internet Of Things In Retail markets by type, Beacons, RFID Tags, Sensors, Wearables & Others] and by regions [In North America, In Latin America, Europe, The Asia-pacific, Middle East and Africa (MEA), What are the main countries covered?, The United States, Canada, Germany, France, UK, Italy, Russia, China, Japan, Korea, Southeast Asia, India, Australia, Brazil, Mexico, Argentina, Chile, Colombia, Egypt, Saudi Arabia, United Arab Emirates, Nigeria & South Africa]
3. What value addition does Country landscape will provide? —> In the premium version of report, two-level of regional segmentation allows user to have access to country level break-up of market Size by revenue and volume* * Wherever applicable
Read more: https://newsmantraa.us/internet-of-things-in-retail-market-may-see-a-big-move-ibm-impinj-allerin-tech/#ixzz74ktW5Kbe

Chad Sweet is the Co-Founder and CEO of ModalAI, a San Diego based provider of AI-powered computing platforms for autonomous drones and robots that communicate via 4G and 5G cellular networks. ModalAI was spun out of wireless technology provider Qualcomm in 2018. Prior to founding ModalAI, Sweet was Senior Director of Engineering in Qualcomm’s Robotics R&D Group. He also held various engineering positions during his 20 years at Qualcomm, with 15 patents granted during that time. In February, Sweet was elected to the Board of Directors of The Dronecode Foundation, a vendor-neutral foundation for open source drone projects.
In April 2020, ModalAI released VOXL Flight, a development platform for GPS-denied autonomous drone localization and navigation, along with computer vision for AI-powered object recognition, depth sensing and obstacle avoidance. The SWaP-C (size, weight, power consumption, and cost) optimized VOXL Flight incorporates a Qualcomm Snapdragon SoC and PX4 flight controller on a single board, and can support up to four image sensors for simultaneous 4k video capture, streaming and machine vision processing. An LTE Add-on is available that plugs in to the VOXL’s board to board connector enabling command and control for operations beyond visual line of sight (BVLOS). ModalAI’s VOXL Flight was a 2021 RBR50 Robotics Innovation Award honoree.
Chad Sweet was recently interviewed by Oliver McClintock for My Dear Drone. That interview is reprinted below, with minor modifications. The original interview can be found HERE.

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Oliver McClintock – Welcome Chad Sweet, tell us on yourself and your backstory?
Chad Sweet – After a long career in R&D engineering at Qualcomm in San Diego, in June 2018, Donald Hutson and I spun out the robotics R&D project into a separate company, ModalAI. I’m passionate about pushing the boundaries of the latest technologies, specifically autonomous vehicles. Robots excite me as the advances are so tangible. You make a change, and the results are immediately visible.
After receiving my Bachelor of Engineering in computer engineering at Vanderbilt University in 1998, I started at Qualcomm Inc. There I ultimately led global robotics R&D at Qualcomm Research working on multiple autonomous robotics product launches, including Sony Aibo, Hover Camera, Snapdragon Flight, and Ecovacs DJ35. Previously to that, I led efforts in computer vision and wireless communications. In total, I’m named on 15 patents.
Oliver McClintock – How did you get going in the robotic and drone markets?
Chad Sweet – At Qualcomm, I was an early leader in the computer vision efforts, some of which evolved into Vuforia and FastCV. I had the opportunity to work on a novel, neuromorphic approach to robotics, and I jumped on it. Autonomous robotics can be considered computer vision, so it was exciting to approach some older problems in a new environment.
That neuromorphic project transitioned to bringing Snapdragon to the robotics market. We quickly saw consumer drones as a growing market and addressed the market with Snapdragon Flight, the smallest high-performance computing platform for drones at the time.
Oliver McClintock – Tell us about your ModalAI company, what is it, and what motivated you to launch it?
Chad Sweet – ModalAI builds on the R&D we were doing at Qualcomm. We are making the smallest, most advanced flight control and communication systems for drones. ModalAI continues to advance the technology we developed at Qualcomm by commercializing more AI software and hardware. We have heavily invested in the open-source communities Dronecode and ROS. ModalAI’s goal is to make our platform as open as possible so that developers can integrate their novel applications on the platform as efficiently as possible.
Continue reading: https://www.roboticsbusinessreview.com/interview/flight-control-and-communication-for-autonomous-drone-navigation-an-interview-with-modalai-ceo-chad-sweet/

A number of countries across the world increasingly are turning to wind generated electricity as a way to combat climate change, creating new opportunities for the commercial drone industry and related businesses.
Using artificial intelligence (AI)-enabled drones and software, Nearthlab, a South Korea-based start-up company hopes to carve out a niche for itself in the rapidly growing global wind turbine inspection market.
“Amid the green energy boom, drone inspection has become a favorable option for the owners and operators of wind farms,” Jay Choi, Nearthlab’s CEO and co-founder, said in an interview.
With its autonomous drones, Nearthlab can conduct a drone inspection for a wind turbine in around fifteen minutes, far less time than that required for other inspection methods. The drone’s AI software allows the unmanned aerial vehicle to recognize the shape and position of the turbine’s blades and calculate the optimal flight path to conduct the inspection.
“Using computer vision and AI software, the drone consistently flies along the blade while maintaining a close and constant distance to capture the smallest details,” Choi said. During its flight, the drone collects data and takes high-resolution photos. Then it uploads the information package to a data management platform for analysis.
Once the data is received, the data management platform’s AI software will analyze it in order to detect any potential damages to the blades, and if it finds any defects the software will accurately determine the size and location of the damage, Choi said.
“The inspectors can utilize this data to help them manage the overall operations, the maintenance and repair jobs,” he said.
Combining space-age and down-to-earth technologies: drone inspection for wind turbines
Choi combined his education with aerospace engineering, with experience in the construction industry to come up with the inspiration for launching Nearthlab. A graduate of the Korea Advanced Institute of Science and Technology, Choi said he had first become interested in aerospace upon visiting NASA when he was younger. “I had a dream of making robots and rovers and exploring space,” he said.
After graduation, he worked as a process control and system engineer for Doosan Heavy Industries & Construction Co., where he learned that one of the most difficult and dangerous jobs on a construction site was infrastructure inspection.
“Back then it was common to see people climbing to reach the top of the chimney that soars over 300 feet, and they would be hanging to the structure by a single rope,” he said. “That’s when I started to see the potential for drones.”
Continue reading: https://dronelife.com/2021/08/26/drone-inspections-for-wind-turbines-in-as-little-as-15-minutes-korean-drone-software-company-nearthlab/

We all know there are a whole lot more men than women in the European tech world, and that it’s often the men talking the loudest on social media platforms. 
But there are a growing number of powerful female voices making themselves heard.
With the help of LinkedIn’s UK team, we’ve tracked down female tech leaders in Europe who regularly share thought-provoking, useful and smart posts on LinkedIn. 
Who are they –– and how did their entrepreneurial journey begin?  
If you want to suggest someone, please email us at [email protected]. 
Alice Zagury –– CEO of startup community The Family 
What’s her story? Zagury has been supporting startup founders since she graduated back in 2008. She spent three years at Silicon Sentier, a startup community in Paris, mentoring international entrepreneurs raising funding and gaining visibility. 
In 2012, she cofounded The Family with Lebanese entrepreneur and business angel Oussama Ammar, to create an accelerator that would make entrepreneurship more accessible. Since then, they’ve built a network of 800+ founders and are now enrolling startups from around the world. 
What about her LinkedIn posts? Startup news and tips, events and content about entrepreneurship (in English and French).
LinkedIn network: 45k
Mette Lykke –– Cofounder and CEO of Too Good To Go
What’s her story? Lykke built her first business out of her love for fitness: Endomondo, a social fitness app that was acquired by US apparel company Under Armour in January 2015. She worked there for two years as VP international and left to start her second venture: food-waste app Too Good To Go. 
Since 2017, the app has grown to a team of 750+ people, works with 500+ retail partners and is active in 15+ western countries. It recently launched in Canada. 
What about her LinkedIn posts? Food waste, the global food supply chain and building a sustainable business.
LinkedIn network: 31k+
Anna Alex –– Cofounder and CCO of Planetly and cofounder of Outfittery
What’s her story? With a background in product management, Alex started her first company Outfittery, a personal shopping service, with Julia Bösh in 2012. She oversaw product, management and operations as co-CEO. 
She left in 2019 to launch Planetly, a platform that tracks, measures and reduces companies’ carbon footprints. Last April, it raised €5.2m and is backed by European VCs Speedinvest and Cavalry Ventures. 
What about her LinkedIn posts? She covers climate tech and sustainability in business and posts a positive climate news recap every Friday (in English and German).
Continue reading: https://sifted.eu/articles/europe-female-startup-linkedin/

Women’s Equality Day offers an annual reminder of the discrepancies that continue to exist between men and women, even in Western nations like the US. The awareness day takes place on August 26, marking the date the 19th Amendment to the US Constitution was passed in 1920, granting full suffrage to women. While it’s clear that women’s rights have improved considerably since that time within the legal frameworks of the US, the reality is that women continue to be significantly underrepresented in many of the top professions and positions of influence in society.
“On Women’s Equality Day, we celebrate women gaining the right to vote, but we can’t lose sight of the fact that gender inequality still exists today. Women in leadership remain underrepresented, and gender biases are prevalent across all industries,” commented Julie Giannini, chief customer officer, Egnyte.
This issue is highlighted to no small degree in the cybersecurity and broader technology sector. An ISC2 study last year found that while almost a third of the global cybersecurity workforce is now female, women receive 21% less pay than their male counterparts on average. Additionally, Eskenzi PR and Marketing research published on International Women’s Day (IWD) 2021 found that just 10% of board positions and 16% of management roles in the industry are held by women.
While various factors may help explain such figures, evidence suggests that workplace cultures and sexist attitudes are a major reason for these inequities. For example, research from the Chartered Institute of Information Security (CIISec) earlier this year revealed that 48% of women in the cyber industry had been made to feel unwelcome in a “boys only club.” In addition, 47% said they had observed or experienced sexism in the workplace.
Ensuring women have the same opportunities to develop in the sector as their male counterpoints is both morally right and crucial in closing the huge IT skills gap. It is also becoming increasingly recognized that a diverse range of perspectives is required to ensure new ideas and innovation can flourish in this sector.
So what needs to change to ensure that women can compete just as well as men in the cyber and technology industry?
Firstly, women working in the sector should not be reluctant to seek help from others to navigate their careers, according to Michelle Fitzgerald, director of demand gen and events, Plutora.
“My hope for other women in tech is to not only take an active role in your own career but also focus on connecting and building relationships with other women,” she outlined. “Building connections, seeking out a mentor or becoming a mentor yourself are all rewarding ways to continue to grow, learn and lead. We can all benefit from building relationships that challenge us and help us to thrive personally and professionally.
“Since becoming a mother in addition to a working professional, the support of family, friends and colleagues has been instrumental in my success in the workplace. In order to progress and really drive forward issues related to women’s equality, we also have to keep ourselves whole. That means different things to different people; for me, it’s maintaining a good work-life balance. With two demanding kids myself, I’ve found that setting clear boundaries between work, family and personal time have allowed me to minimize stress and maximize productivity.”
Continue reading: https://www.infosecurity-magazine.com/news-features/opportunities-women-tech/

One question these professions should be asking is: Which technology will create the most impactful transformation — artificial intelligence (AI), robotic process automation (RPA), cloud use, or blockchain?
Cloud and RPA have the ability to solve many process and capacity challenges, and that explains the tremendous adoption growth we have seen over the past year and a half. AI is appearing in more operating systems and software solutions that are used by the tax & accounting profession. And AI promises to augment the deep knowledge and analysis that is expected from industry professionals.
However, that often means that the impact of blockchain is being underestimated by many in accounting. Although many are aware of the term blockchain, many people are still quite uncertain what it means fully, which makes it more difficult to imagine the transformation it can and is driving. To be future-ready is to be aware, adaptive, and predictive.
Indeed, there are predictions that blockchain will be the new operating system at some point in the future — are you aware and adapting to these changes?
Being aware
In short, blockchain is a decentralized, secure, distributed ledger; and the name comes from the way the data is structured in blocks. As data is added to the blockchain it is verified by everyone in the chain. Blockchains can be public, such as with Bitcoin, or private. The use cases are continuing to emerge as blockchain creates greater transparency and allows for more verification of both sides of a transaction.
Worldwide spending by organizations on blockchain solutions has grown to more than $6.6 billion in 2021, and is expected to reach almost $19 billion by the end of 2024. The total crypto market capitalization has reached $1.88 trillion, as of August 2021.
As banks around the world invest in blockchain technology, the largest use case has become cross-border payments and settlements.
Continue reading: https://www.reuters.com/legal/transactional/tax-accounting-firms-time-learn-blockchain-is-now-2021-08-20/

Blockchain has been heralded as a cutting-edge technology that will improve the contemporary supply chain structure by increasing supply chain trust, efficiency, and transparency. However, as promising as blockchain technology is, blockchain is not a panacea for supply chain issues. There are numerous pros and cons of using blockchain in the supply chain:
 

• Trust. Because data on the blockchain is decentralized and immutable, members of the supply chain can trust the data they see on the blockchain. Conversely, a traditional supply chain data storage structure typically requires all members of the supply chain to keep their own records, and therefore disputes arise when those records do not match up.
• Efficiency. Because all data is recorded at every step in the supply chain, and every member of the supply chain can see the data, it is easy to quickly identify where in the supply chain a nonconformance (e.g., a product defect or missing product quantity) has occurred, because the life cycle of a product is tracked at every step. Let’s take, for example, the construction of a refrigerator. In the case of a traditional supply chain structure, if the refrigerator manufacturer discovers that the compressor of a finished refrigerator contains a defective valve, the refrigerator manufacturer will then need to reach out to the compressor manufacturer, who will need to reach out to the manufacturer of compressor components, and so on and so forth, up the supplier tiers until the supplier of the defective valve is reached. In contrast, if all members of the refrigerator supply chain were members of the same blockchain network, the refrigerator manufacturer would be able to query the blockchain to find the entire tracing history of the defective valve almost instantaneously, cutting investigation time down considerably. Using blockchain technology allows for less time lost sending emails and making phone calls to find out the cause of the nonconformance. Additionally, because documents are stored on a shared ledger, physical paperwork is largely unnecessary.
• Transparency. Blockchain engenders transparency because all data on the blockchain is recorded automatically with a time stamp, including certain data that usually would not be recorded in a traditional supply chain system (such as the steps completed in a production process or the time of a seller’s receipt of a purchase order). Blockchain technology also creates transparency by enabling end-to-end tracking (i.e., traceability from one end of the supply chain to the other), which can be enjoyed by all supply chain members on the blockchain. Blockchain transparency can accomplish quicker resolutions to disputes than with traditional supply chain systems.

Continue reading: https://www.natlawreview.com/article/pros-and-cons-blockchain-supply-chain

The past decade saw artificial intelligence (AI) advance by leaps and bounds. From the birth of Alexa to its application in vaccine development, AI has radically altered our personal and professional lives. Now, it’s seemingly everywhere — including in travel apps, streaming services, parking garages and delivery robots. 
AI’s range of use cases is a testament to its widespread value, but the technology does not magically work “out of the box.” It still needs humans to learn, to stay relevant and to serve as a backup when needed — no matter the use case. In fact, I believe there will always be a place for both human and machine intelligence in successful AI deployment because what comes naturally to people, like interpersonal skills and judgment, is difficult for machines — while analyzing mountains of data at scale is nearly impossible for people. 
Today, many companies leverage some combination of the two. There’s a fine line to walk between leaning on the technology too much and not enough, but getting it right can pay dividends. In a 2018 PwC study, 82% of top-performing companies reported paying close attention to the human experience with digital and tech. As brands across industries aim to do the same, here are four strategies for blending artificial and human intelligence to unlock the full potential of both:
Recognize that AI doesn’t work all on its own.
AI has gotten really good at transcribing speech, diagnosing diseases and fielding frequently asked questions — but it can’t do everything. This can be a tough pill for companies to swallow. Why can’t technology that has seen billions of dollars in investment stand on its own? Because that’s not the real goal of today’s AI. 
AI can be one piece of the puzzle but should never be mistaken for the only piece. Take the current state of autonomous vehicles as an example; some still interpret a cloud of dust as a solid object and may stop to accommodate it. We could hone and perfect this technology for 20 more years and still not account for every unexpected obstacle, weather pattern or driver behavior on the road. We have to recognize how AI fits into the broader picture to unlock its value — it’s not a perfect panacea, but it can be part of a solution.
Don’t be afraid to challenge conventional thinking about the need for humans in certain roles.
I believe humans will always play a vital role in AI deployments and training, but companies can’t always afford, scale or even find human workers. Today, efficiency and convenience are top priorities for customers, according to the aforementioned PwC report. In customer service, for instance, I've found that people want fast and easy answers — and often don’t care whether they speak with a person to get them. In a recent survey my company conducted, two-thirds of consumers reported that they are comfortable speaking with an AI-powered customer service solution if they can speak normally and get their problem resolved quickly. 
In fact, I think businesses often underestimate how comfortable people are with AI. The same survey found that 76% of people are comfortable with hospitals using AI-powered disinfectant robots, and 66% are comfortable seeing a robot at the grocery store for functions like cleaning up spills or restocking shelves. 
There’s a role for AI and a role for humans, but both seem to be evolving. 
Continue reading: https://www.forbes.com/sites/forbescommunicationscouncil/2021/08/26/better-together-striking-the-balance-between-artificial-and-human-intelligence/?sh=2ac31f733ab2

On-demand, scalable, and economic cloud storage and computation has enabled the efficient processing of huge data sets to draw critical insights using Artificial Intelligence (AI). Launching multiple AI initiatives is par for the course today. After all, some will not succeed. But how do you choose where to devote your resources?
"With so many options, the most difficult part can be deciding where to invest first."
“It is near impossible to name an industry that isn’t implementing AI solutions nowadays given its breadth of applications,” says Jim Radzicki, CTO of Telus International. “But, with so many options, the most difficult part can be deciding where to invest first.” There are so many areas where AI can be applied and demand for intelligent capabilities in the enterprise continues to grow, says Peter A. High, author of Getting to Nimble: How to Transform your Company into a Digital Leader and president of the technology and business advisory firm Metis Strategy.
AI project prioritization is critical. “It ensures that AI is connected to the business’ agenda and priorities,” says Goutham Belliappa, vice president of AI engineering at Capgemini North America. “Through tight governance and monitoring, companies can identify which projects are performing better than others and adjust the prioritization and resources accordingly in an agile manner.”
AI project prioritization: 6 strategies
Prioritization provides a framework wherein leaders can review all the options and available resources to determine the order in which AI projects will be implemented. “This type of big picture approach helps businesses achieve long-term success by taking all factors into consideration and making thoughtful decisions as opposed to executing them on an ad hoc basis,” Radzicki says. “Understanding the potential missed opportunities foregone by choosing one project implementation over another allows for better decision-making.”
Consider these six tips for AI project prioritization:
1. Focus on business significance
Buy-in from the board and C-suite is paramount. “If projects are tied to high-priority, tangible business outcomes, then they are more likely to succeed,” says Belliappa. Tie all AI initiatives into the business strategy of the enterprise and divisions of the company.
This “helps ensure that you do not develop AI for AI’s sake,” says High, “which can be another pathway to problems.”
Continue reading: https://enterprisersproject.com/article/2021/8/how-prioritize-artificial-intelligence-ai-projects-6-tips

The rhetoric surrounding artificial intelligence (AI) as the panacea for solving business problems has created some skepticism among marketers. It can also be overwhelming.
AI might seem like a cure-all for the issues with your data or marketing and sales analytics. In reality, the technology is none of these things, and AI applications can be classified into several categories, depending on the purpose. There are three “AI’s” that I believe are critical for marketers:
• Automated integrations of data, processes and external events intelligence to enable faster and real-time decision-making.
• Actionable intelligence for organizations, powered by a powerful platform for developing insight.
• Augmented intent data that aggregates multiple data types per market to ensure that it can be easily understood and used by marketing and sales organizations.
For certain, the use of AI by marketers is taking hold. Revenue increases from adopting AI are reported most often in marketing and sales, while other benefits include the ability to predict the likelihood of buying, cost reductions and customer service analytics, according to McKinsey. And with projections that the global enterprise AI market will reach $53.06 billion by 2026, it’s too tantalizing not to consider the transformational potential of AI and machine learning for B2B marketing.
AI has clearly moved beyond the hype; algorithms are continuously learning and can self-correct, giving them the ability to transform work and create a competitive advantage.
Understanding AI’s potential and its benefits can help you and your business benefit from the technology rather than being overwhelmed by it. To prepare, businesses should standardize their definition of AI, assess their readiness for AI solutions and define measurable and transparent ROIs for AI initiatives.
Here are five ways I believe B2B marketers will use AI in the next few years:
Increase lead generation capabilities. One of the core functions of AI is the ability to collect data and extract insights — in this case, from marketing and sales data using machine learning and predictive analytics. Additionally, some AI tools can provide insights about prospects and customers to improve the customer experience and conversion rates.
Gain more actionable customer insights. AI is used to gather information and analyze it to engage more effectively with customers and prospects. Predictive analytics will help forecast purchasing decisions based on buying patterns. This is important and immensely useful because it’s harder to see buying patterns in a B2B model than in a B2C one.
Continue reading: https://www.forbes.com/sites/forbesagencycouncil/2021/08/26/five-ways-artificial-intelligence-will-change-the-b2b-marketing-industry-in-the-next-four-years/?sh=3c9d9c4b50b2

Women’s Equality Day is an important opportunity for businesses to take a step back and evaluate if they are doing everything they can to have a diverse and equal workforce. Within the technology industry, only 1 in 6 specialists in the UK are women and the growth of female representation in the sector has stalled over the last ten years. But what is the reason for this and how do we encourage women to join such male-dominated industries? Open Access Government has spoken to four technology industry leaders to try and find the answers.
Outnumbered and underrepresented
Women working in male-dominated industries compete with obstacles on a day to day basis as they fight for their voices to be heard.
“Despite Women’s Equality Day coming round every year, the proportion of female workers in tech industries is still not increasing at a significant rate. 72% of women in tech roles still report being regularly outnumbered by men in business meetings by at least a 2:1 ratio, and 26% of women put this ratio as 5:1 or more,” explains Leane Parsons, Change Manager at Node4.
“The situation is clearly still not improving, tracking right back to schools and classrooms. Whilst it is encouraging to see an increase in the number of students taking STEM subjects into higher education, there are still significantly more boys choosing this academic pathway and the number of girls studying Computing remains worryingly low. With the skills shortage in the technology sector continuing to increase, this lack of uptake should remain a cause for concern for the industry.
With the tech sector remaining such a male-dominated industry despite best efforts to reverse this trend, it is disappointing to see that despite a 40% growth in employment within UK tech companies in the last two years, just 30% of these roles were occupied by women. It is hard to imagine how this might change without more girls taking subjects such as Computing and programming into higher education and beyond.”
Ann Lloyd, VP Customer Success & Experience at Axway adds that, “although women represent nearly half of the entire workforce today, they’re still massively underrepresented in the technology industry. What’s more, McKinsey’s 2020 Women in the Workplace study found that the pandemic has negatively impacted women more severely than men, and we’ll continue to see its ripple effects into the future, undoing much of the progress made over the past six years.”
“Despite it being over one hundred years since women got the right to vote in the UK, it’s sobering to realise that women are still underrepresented in many areas of life including with which subjects they choose to study, which career they pursue and even how much they get paid, relative to their male peers. Although there are no official statistics on the percentage of women in data science or AI roles, there is growing evidence that the gender imbalance that affects the tech sector extends to data science and AI, as well,” furthers Martin Rehak, Founder & CEO at Resistant.AI.
However, it is important to recognise that it is not all doom and gloom and that progress has been, and is continuing to be, made.
“I was encouraged by a February report from the Office of National Statistics (ONS) which stated that 31% of UK tech jobs were held by women. This represents progress when it comes to gender equality in the workspace, but I believe that organisations still need to be proactive in ensuring women are represented in IT professional and leadership roles,” explains Liz Cook, Chief People Officer at Six Degrees.
Continue reading: https://www.openaccessgovernment.org/womens-equality-day-breaking-the-gender-bias-in-male-dominated-industries/118379/

Dive Brief:

• Two-thirds (68%) of businesses feel there's a lack of diversity in their technology workforce, but less than half (46%) are actively addressing the issue within tech teams, according to a WILEY survey of more than 2,000 early career tech workers and 270 business leaders released earlier this month.
• Half of young tech workers reported leaving or wanting to leave a tech job because the company culture made them feel uncomfortable or unwelcome. Among women of color surveyed, the number increases to 57%. 
• The discomfort among underrepresented tech workers starts early in the hiring process. Six in 10 (64%) survey respondents believe the technology job recruitment process discriminates against people from minority backgrounds.

Dive Insight:
To support a diverse workforce, ingraining inclusivity into workplace culture aligns the effort to business missions to support long-term development.
"When organizations seek to provide a wide variety of minds with the right training and opportunities, they will organically increase the talent pool and attract a diverse group of candidates," Jesse Kinser, CISO at Pathwire, said in an email.
Continue reading: https://www.ciodive.com/news/wiley-survey-diversity-equity-inclusion/605589/

Named one of the Most Influential Women in UK Tech and Most Influential Women in Cybersecurity, Sarah is also a firm supporter of female representation in technology industries. She is regularly booked for corporate conferences and events, to speak from the perspective of a woman in business and highlight the importance of diverse thoughts.
With the support of The Female Motivational Speakers Agency, we sat down with Sarah to learn more about digital transformation, cybersecurity and workplace diversity.
You have been the Chief Security Advisor at Microsoft Europe since 2020, what has been your proudest achievement in this role?
For me, I actually joined Microsoft one week after the UK went into lockdown. So I’ve actually spent my entire Microsoft career to date from this very office! It’s been quite interesting for me to be literally in the middle of a global pandemic, joining a new company, but also seeing the inner workings of Microsoft.
Throughout everything going on, we had to keep Microsoft up as an entity – Microsoft has over 160,000 people worldwide. But they also had to make sure the current customers were supported, and that’s all of the global Cloud and the data centers and all of those types of things. Because of the pandemic, we’ve seen a massive acceleration to the Cloud as well, particularly collaboration sites like Teams, and those types of things.
Continue reading: https://www.maddyness.com/uk/2021/08/25/microsofts-sarah-armstrong-smith-on-cybersecurity-digital-transformation-and-diversity/