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Despite acknowledged promise: Fear, uncertainty and doubt surround AI adoption

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Global research from Juniper Networks shows consumers and enterprises want more artificial intelligence, but why are three challenges continuing to hinder pulling the trigger?

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Image: iStock/metamorworks

Executives worldwide placed artificial intelligence as a top strategic priority for 2021, yet plans have slowed or been curtailed. Juniper Networks recently released the report, “AI is set to accelerate…is your organization ready?” which addresses this very curious dilemma: Developers, organizations (95%) and consumers know the benefits, welcome and are excited about the potential. But how can companies accelerate their adoption? 

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Today’s AI

Today, AI’s slow rollout includes the automation of daily tasks, such as chatbots for customer service, bank reconciliations and smart workflows for IT trouble ticket management. The aforementioned 95% of organizations believe their companies would benefit from embedding AI into daily operations, products and services. Curiously though, only 6% of C-level leaders reported adoption of AI-powered solutions across their organizations today.

“I wasn’t all that surprised by the findings because the challenges are real and ones that come up in my discussions with other CIOs on the topic,” said Sharon Mandell, senior vice president and CIO of Juniper Networks. “There are always challenges with new technology, but these concerns should not hold people back from experimenting, learning, moving forward and getting the real benefits that are there. Start by dipping your toes in the water and work to get comfortable before swimming into the deep end.”

SEE: Digital transformation: A CXO’s guide (free PDF) (TechRepublic)

The top three challenges to embraceable AI adoption

Juniper found the gap lies within the following three challenges, ranked by respondents as the most prescient adoption inhibitors: AI-ready technology stacks, workforce readiness and AI governance.

Respondents were asked to rank developing company value-added AI models and data sets considered “the top technology-related challenge.” Ingesting, processing and managing data to feed AI is their No. 1 tech challenge, Juniper’s report stated. Financial commitment is essential “in robust cloud solutions and preparation of the right data for AI to use;” 39% of respondents said they’re “likely to collect telemetry data to enhance AI to improve user experience, as well as ensure sensitive data is protected in the process.” Thirty-four respondents said AI tool capabilities are the most critical to enable AI adoption.

Getting the workforce onboard: 73% of organizations struggle with the preparation and expansion of their workforce to integrate with AI systems. It’s the highest priority for the company, C-level respondents reported, to hire people to develop AI capabilities within an organization than it is to train end-users to operate the tools themselves.  

Under the right umbrella: 67% of respondents reported that AI has been identified as a priority by their organizations’ leaders for a fall 2021 strategic plan, and 87% of executives agree that organizations have a responsibility to have governance and compliance policies in place to minimize negative impacts of AI, yet executives still ranked establishing AI governance, policies and procedures as one of their lowest priorities. A further 84% of executives agree cross-functional executive sponsorship and involvement is critical for AI to integrate into their products and services. Yet only 7% of executives said they haven’t identified a company-wide AI leader to oversee AI strategy and governance. Seventy-four percent of respondents agree that employee satisfaction has increased since implementing AI solutions to assist in their operational tasks.

What AI there is, is very good

The organizations that are early AI adopters cite positive changes like operational efficiencies and enhanced user-experience. Juniper’s research found companies that “adopted and harnessed AI are showing real and meaningful outcomes, providing optimism and excitement.”

Further research found that as organizations scale their AI capabilities and integrate employees into solutions, user satisfaction steadily rises, and time saved allows employees to focus on value-added tasks that were previously unmanageable.

How to keep competitive

To keep competitive, the industry needs to “Adapt!” Mandell said. “Organizations have only just begun to understand the integration challenges and investment required for AI-ready technology stacks. Ultimately, they need the proper infrastructure as their base foundation for AI. Once they’ve built the proper base to ingest and process quality and unbiased data, they should focus on ensuring their workforce is armed with the proper skills and tools to support this AI wave. Finally, when it comes to AI adoption, governance, cross-functional and executive involvement are all critical to ensure that AI stays within the business’ priorities.”

AI’s future in business

Looking forward, Mandell said, “While a lot of the fear around AI might still exist, it has the power to unlock our workforce, to enable businesses, to change the world. While there are some barriers to adoption, the optimism around the use of AI in organizations is palpable; AI in the enterprise is set to take off. With almost two-thirds of the organizational leadership surveyed noting that AI is a top priority for their 2021 strategic plans, we can not only expect to see more trials and deployments in the near future, but also watch as AI becomes essential to the business of tomorrow.”

Methodology: Juniper surveyed 700 IT global decision makers who have direct involvement in their organization’s AI and/or machine-learning plans or actual deployments to assess the attitudes, perceptions and concerns of the technology.

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Source: https://www.techrepublic.com/article/despite-acknowledged-promise-fear-uncertainty-and-doubt-surround-ai-adoption/#ftag=RSS56d97e7

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Falsified Satellite Images in Deepfake Geography Seen as Security Threat

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Scientists who have identified a potential national security threat from deepfake geography, such as in false satellite images, are studying ways to identify them and take countermeasures. (Credit: Getty Images)

By John P. Desmond, AI Trends Editor

Deepfake is a portmanteau of “deep learning” and “fake”, and refers to a synthetic media usually in which a person in an existing image or video is replaced with someone else’s likeness. Deepfakes use techniques from machine learning and AI to manipulate visual and audio content with a high potential to deceive.

Deepfakes applied to geography have the potential to falsify satellite image data, which could pose a national security threat. Scientists at the University of Washington (UW) are studying this, in the hopes of finding ways to detect fake satellite images and warn of its dangers.

Bo Zhao, Assistant Professor of Geography, University of Washington

“This isn’t just Photoshopping things. It’s making data look uncannily realistic,” stated Bo Zhao, assistant professor of geography at the UW and lead author of the study, in a news release from the University of Washington. The study was published on April 21 in the journal Cartography and Geographic Information Science. “The techniques are already there. We’re just trying to expose the possibility of using the same techniques, and of the need to develop a coping strategy for it,” Zhao stated.

Fake locations and other inaccuracies have been part of mapmaking since ancient times, due to the nature of translating real-life locations to map form. But some inaccuracies in maps are created by the mapmakers to prevent copyright infringement.

National Geospatial Intelligence Agency Director Sounds Alarm

Now with the prevalence of geographic information systems, Google Earth and other satellite imaging systems, the spoofing involves great sophistication and carries more risks. The director of the federal agency in charge of geospatial intelligence, the National Geospatial Intelligence Agency (NGA), sounded the alarm at an industry conference in 2019.

“We’re currently faced with a security environment that is more complex, inter­connected, and volatile than we’ve experienced in recent memory—one which will require us to do things differently if we’re to navigate ourselves through it successfully,” stated NGA Director Vice Adm. Robert Sharp, according to an account from SpaceNews.

To study how satellite images can be faked, Zhao and his team at WU used an AI framework that has been used to manipulate other types of digital files. When applied to the field of mapping, the algorithm essentially learns the characteristics of satellite images from an urban area, then generates a deepfake image by feeding the characteristics of the learned satellite image characteristics onto a different base map. The researchers employed a generative adversarial network machine learning framework to achieve this.

The researchers combined maps and satellite images from three cities—Tacoma, Seattle and Beijing—to compare features and create new images of one city, drawn from the characteristics of the other two. The untrained eye may have difficulty detecting the differences between real and fake, the researchers noted. The researchers studied color histograms and frequency, texture, contrast, and spatial domains, to try to identify the fakes.

Simulated satellite imagery can serve a legitimate purpose when used to represent how an area is affected by climate change over time, for example. If there are no images for a certain period, filling in the gaps to provide perspective can provide perspective. The simulations need to be labeled as such.

The researchers hope to learn how to detect fake images, to help geographers develop data literacy tools, similar to fact-checking services. As technology continues to evolve, this study aims to encourage more holistic understanding of geographic data and information, so that we can demystify the question of absolute reliability of satellite images or other geospatial data, Zhao stated. “We also want to develop more future-oriented thinking in order to take countermeasures such as fact-checking when necessary,” he said.

In an interview with The Verge, Zhao stated the aim of his study “is to demystify the function of absolute reliability of satellite images and to raise public awareness of the potential influence of deep fake geography.” He stated that although deepfakes are widely discussed in other fields, his paper is likely the first to touch upon the topic in geography.

“While many GIS [geographic information system] practitioners have been celebrating the technical merits of deep learning and other types of AI for geographical problem-solving, few have publicly recognized or criticized the potential threats of deep fake to the field of geography or beyond,” stated the authors.

US Army Researchers Also Working on Deepfake Detection

Professor C.-C. Jay Kuo, Professor of Electrical and Computer Engineering, University of Southern California

US Army researchers are also working on a deepfake detection method. Researchers at the US Army Combat Capabilities Development Command, known as DEVCOM, Army Research Laboratory, in collaboration with Professor C.C. Jay Kuo’s research group at the University of Southern California, are examining the threat that deepfakes pose to our society and national security, according to a release from the US Army Research Laboratory (ARL).

Their work is featured in the paper titled “DefakeHop: A light-weight high-performance deepfake detector,” which will be presented at the IEEE International Conference on Multimedia and Expo 2021 in July.

ARL researchers Dr. Suya You and Dr. Shuowen (Sean) Hu noted that most state-of-the-art deepfake video detection and media forensics methods are based upon deep learning, which has inherent weaknesses in robustness, scalability, and portability.

“Due to the progression of generative neural networks, AI-driven deepfakes have advanced so rapidly that there is a scarcity of reliable techniques to detect and defend against them,” You stated. “We have an urgent need for an alternative paradigm that can understand the mechanism behind the startling performance of deepfakes, and to develop effective defense solutions with solid theoretical support.”

Relying on their experience with machine learning, signal analysis, and computer vision, the researchers developed a new theory and mathematical framework they call the Successive Subspace Learning, or SSL, as an innovative neural network architecture. SSL is the key innovation of DefakeHop, the researchers stated.

“SSL is an entirely new mathematical framework for neural network architecture developed from signal transform theory,” Kuo stated. “It is radically different from the traditional approach. It is very suitable for high-dimensional data that have short-, mid- and long-range covariance structures. SSL is a complete data-driven unsupervised framework, offering a brand-new tool for image processing and understanding tasks such as face biometrics.”

Read the source articles and information in a news release from the University of Washington, in the journal Cartography and Geographic Information Science,  an account from SpaceNews,a release from the US Army Research Laboratory, and in the paper titled “DefakeHop: A light-weight high-performance deepfake detector.”

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Source: https://www.aitrends.com/ai-in-science/falsified-satellite-images-in-deepfake-geography-seen-as-security-threat/

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Data Science is Where to Find the Most AI Jobs and Highest Salaries

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AI is a hot job market and the hottest jobs in AI are in data science. And data science jobs also pay the highest salaries. (Credit: Getty Images)

By John P. Desmond, AI Trends Editor

Jobs in data science grew nearly 46% in 2020, with salaries in the range of $100,000 to $130,000 annually, according to a recent account in TechRepublic based on information from LinkedIn and LHH, formerly Lee Hecht Harrison, a global provider of talent and leadership development.

Related job titles include data science specialist and data management analyst. Companies hiring were called out in the TechRepublic account, including:

Paul Anderson, CEO, Novacoast

Novacoast, which helps organizations build a cybersecurity posture through engineering, development, and managed services. Founded in 1996 in Santa Barbara, the company has many remote employees and a presence in the UK, Canada, Mexico, and Guatemala.

The company offers a security operations center (SOC) cloud offering called novaSOC, that analyzes emerging challenges. “We work to have an answer ready before we’ve been asked,” stated CEO Paul Anderson in a press release issued on the company’s inclusion on a list of the top 250 Managed Service Providers from MSSP Alert. novaSOC automatically collects endpoint data and correlates it with threat intelligence sources, adding in analysis and reporting to make a responsive security monitoring service. Novacoast is planning to hire 60 employees to open a new SOC in Wichita, Kansas.

Pendo is an information technology services company that provides step-by-step guides to help workers master new software packages. The software aims to boost employee proficiency through personalized training and automated support. Founded in 2013 in Raleigh, N.C., the company has raised $209.5 million to date, according to Crunchbase. Demand for the company’s services soared in 2020 as schools shifted to online teaching and many companies permitted employees to work from home.

“More people are using digital products. Many had planned to go digital but they could not afford to wait. That created opportunities for us,” stated Todd Olson, cofounder and CEO, in an account in Newsweek. The company now has about 2,000 customers, including Verizon, RE/MAX, Health AB, John Wiley & Sons, LabCorp, Mercury Insurance, OpenTable, Okta, Salesforce and Zendesk. The company plans to hire 400 more employees this year to fuel its growth as it invests in its presence overseas in an effort to win more large customers. The company recently had 169 open positions.

Ravi Kumar, President, Infosys

Infosys is a multinational IT services company headquartered in India that is expanding its workforce in North America. The company recently announced it would be hiring 500 people in Calgary, Alberta, Canada over the next three years, which would double its Canadian workforce to 4,000 employees. “Calgary is a natural next step of our Canadian expansion. The city is home to a thriving talent pool. We will tap into this talent and offer skills and opportunities that will build on the city’s economic strengths,” stated Ravi Kumar, President of Infosys, in a press release.

Over the last two years, Infosys has created 2,000 jobs across Toronto, Vancouver, Ottawa, and Montreal. The Calgary expansion will enable Infosys to scale work with clients in Western Canada, Pacific Northwest, and the Central United States across various industries, including natural resources, energy, media, retail, and communications. The company will hire tech talent from fourteen educational institutions across the country, including the University of Calgary, University of Alberta, Southern Alberta Institute of Technology, University of British Columbia, University of Toronto, and Waterloo. Infosys also plans to hire 300 workers in Pennsylvania as part of its US hiring strategy, recruiting for a range of opportunities across technology and digital services, administration and operations.

AI is Where the Money Is

In an analysis of millions of job postings across the US, the labor market information provider Burning Glass wanted to see which professions had the highest percentage of job postings requesting AI skills, according to an account from Dice. Data science was requested by 22.4% of the postings, by far the highest. Next was data engineer at 5.5%, database architect at 4.6% and network engineer/architect at 3.1%.

Burning Glass sees machine learning as a “defining skill” among data scientists, needed for day-to-day work. Overall, jobs requiring AI skills are expected to grow 43.4% over the next decade. The current median salary for jobs heavily using AI skills is $105,000, good compared to many other professions.

Hiring managers will test for knowledge of fundamental concepts and ability to execute. A portfolio of AI-related projects can help a candidate’s prospects.

Burning Glass recently announced an expansion and update of its CyberSeek source of information on America’s cybersecurity workforce. “These updates are timely as the National Initiative for Cybersecurity Education (NICE) Strategic Plan aims to promote the discovery of cybersecurity careers and multiple pathways to build and sustain a diverse and skilled workforce,” stated Rodney Petersen, Director of the NICE, in a Burning Glass press release

NICE is a partnership between government, academia, and the private sector focused on supporting the country’s ability to address current and future cybersecurity education and workforce challenges.

Trends for AI in 2021 in the beginning of the latter stages of the global pandemic were highlighted in a recent account in VentureBeat as:

  • Hyperautomation, the application of AI and machine learning to augment workers and automate processes to a higher degree;
  • Ethical AI, because consumers and employees expect companies to adopt AI in a responsible manner; companies will choose to do business with partners that commit to data ethics and data handling practices that reflect appropriate values;
  • And Workplace AI, to help with transitions to new models of work, especially with knowledge workers at home; AI will be used to augment customer services agents, to track employee health and for intelligent document extraction.

Read the source articles and information in TechRepublic, in a press release from Novacoast, in Newsweek, in a press release from Infosys, in an account from Dice, in a Burning Glass press release and in an account in VentureBeat.

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Source: https://www.aitrends.com/data-science/data-science-is-where-to-find-the-most-ai-jobs-and-highest-salaries/

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Benefits of Using AI for Facebook Retargeting In 2021

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Artificial intelligence has really transformed the state of digital marketing. A growing number of marketers are using AI to connect with customers across various platforms. This includes Facebook.

There are a lot of great reasons to integrate AI technology into your Facebook marketing campaigns. One of the benefits is that you can use retargeting. AI algorithms have made it easier to reach customers that have already engaged with your website. These users might be a lot more likely to convert, which will help you grow your sales and improve your brand image.

AI Can Help Improve Your Facebook Marketing Dramatically with Retargeting

Untapped resources that come from engagement can lead to a better understanding of Facebook retargeting. SAAS SEO agency shared some recommendations that are solid, and a great starting point for any business. To understand Facebook retargeting with AI technology in-depth, take these tips to heart when organizing your resources.

What is Facebook Retargeting?

On average, each Facebook user clicks on ads at least eight times per month. These are considered to be high intent clicks from the biggest advertising platform in the world. Even the most successful marketing and advertising campaigns miss consumers on their first run.

Retargeting uses Facebook campaigns most essential tools to target specific people based on their most relevant data. This is one of the best ways to use data to improve your social media marketing strategies.

The data used is recycled from previous information attached to your old advertising. This includes information from apps, customer files, engagement and offline activity. Anything that has a metric attached to an individual can be used with Facebook retargeting.

How Can It Help Your Business?

There will always be missed opportunities before, during and after a marketing campaign. Reinvesting the data gained from the previous campaign prevents you from starting completely over. Instead of starting from scratch, you’ll gain a clear insight into what gets consumers to cross the finish line at checkout.  Retargeting is meant to be a powerful tool that thrives on previous data that would otherwise go unnoticed.

Retention comes into play, but doesn’t make up the entire story of retargeting on Facebook. You can run a retargeting campaign and only look into new consumers. It’s flexible, and meant to enhance your business based on your specific needs.

The Different Types of Retargeting

The two main types of Facebook retargeting are list-based and pixel-based. Each serves a purpose, with their own specific pros and cons.


Pixel-based retargeting uses JavaScript code to attach a cookie to each unique person that visits your website. After the visitor leaves, the cookie sends its data to your ad provider for a personalized experience. This is the most common type of retargeting used on Facebook, and is often used in other parts of the internet. Microsoft has shown favoritism to pixel-based retargeting by using their own modified version.

List-based retargeting is a limited but fascinating concept. It uses the data you already have on hand to create a specialized list that Facebook uses to show ads. This method works on many of the major social media platforms, but has shown significant advantages on Facebook. Since list-based targeting uses email lists as its base, companies are at the mercy of that particular resource. An outdated or inaccurate email list will lead to low quality retargeting efforts.

When relying on list-based retargeting, a larger email list is not always a guaranteed win for a company.

Upselling and Cross Selling

Even when the customer is happy, proving the value of an upsell is an ongoing process. This led to a rise in cross selling, but was only beneficial to companies that had the resources. As you reconnect with old and new customers, upselling or cross selling becomes part of the closing process.

Both methods are difficult, but become trivial once you have the data to back up your new campaign. Most companies see an increase in profits in a short amount of time. This makes Facebook retargeting a valuable way to test drive upselling and cross selling methods.

Brand Awareness

Brand awareness is the golden goose that all businesses constantly chase. Once you have a notable brand, it becomes the identity of your entire company. Protecting the brand is important, and sometimes entire marketing campaigns are launch to reinvigorate the company image. So, how does Facebook retargeting work its way into this?

Facebook lookalike audiences became a thing when companies wanted to reach new customers with similar interests and habits as their current best customers. Creating a lead that finds this new audience is possible when brand awareness reaches its peak. If you want to keep brand awareness high, then Facebook retargeting does all of the tough work while increasing your reach to new consumers.

Improve Conversions

Conversions are hard to pull off without a specific time investment. All of that goes to waste if you’re not positioning yourself to use previous data to convert customers. No matter how visitors arrive to your website, their presence is proof that there is an interest to purchase a product or service.

If they leave without making a purchase, it’s up to you to figure out why. A lost sale is not the same as losing a customer. Being able to convert that customer into an actual sale is a major strength of retargeting. And even if it’s unsuccessful, you’ll be able to use the additional data to convert another customer.

Influence Buying Decisions

When a consumer becomes firm in their buying decision, then your influence gains a significant bump. At this point your retargeting is directly influencing the buying decisions of individuals or groups. You’ll see a visual representation of this with online feedback and testimonials. All of the positive information provided comes from consumers that are satisfied with the entire sales experience.

Even the negative feedback plays a role, and can serve as the proof you need to reuse data to improve a weak point in your marketing. When a company puts effort into retargeting their ads, they gain monumental increases in customer conversions, ad recognition, clicks, sales and branded searches.

Remarketing Vs. Retargeting

Learn the difference between retargeting and remarketing. Retargeting gains the attention of interested customers that never purchased your products or services. Remarketing leans more towards gaining the attention of inactive or lost customers. Don’t make the mistake of running a retargeting campaign when remarketing would work better. The good news is that the data used from one is still essential for the other. An email list with decent accuracy can be a valuable asset for remarketing or retargeting.

Making the Right Choice

Facebook retargeting should be a priority with how you manage your data collection. Embracing its use will optimize the most important part of your business. Once you get the hang of things, your ROI will reach a whole new level.

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Source: https://www.smartdatacollective.com/benefits-of-using-ai-for-facebook-retargeting/

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Big bank demand for AI talent outpaces supply

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Demand for artificial intelligence (AI) experts at financial institutions continues to grow, with banks looking to leverage digital channels and incorporate data-driven analytics into their workflows as the U.S. economy moves toward reopening. American Express and Wells Fargo led the pack among financial services in AI-related job offerings posted in the past quarter, with the […]

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Source: https://bankautomationnews.com/allposts/center-of-excellence/big-bank-demand-for-ai-talent-outpaces-supply/

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