In praise of knowing the requirements before you start cranking out code

Richard SpeedWed 5 Jun 2024  //  09:25 UTC

A study has found that software projects adopting Agile practices are 268 percent more likely to fail than those that do not.

Even though the researchcommissioned by consultancy Engprax could be seen as a thinly veiled plug for Impact Engineering methodology, it feeds into the suspicion that the Agile Manifesto might not be all it’s cracked up to be.

The study’s fieldwork was conducted between May 3 and May 7 with 600 software engineers (250 in the UK and 350 in the US) participating. One standout statistic was that projects with clear requirements documented before development started were 97 percent more likely to succeed. In comparison, one of the four pillars of the Agile Manifesto is “Working Software over Comprehensive Documentation.”

According to the study, putting a specification in place before development begins can result in a 50 percent increase in success, and making sure the requirements are accurate to the real-world problem can lead to a 57 percent increase.

Dr Junade Ali, author of Impact Engineering, said: “With 65 percent of projects adopting Agile practices failing to be delivered on time, it’s time to question Agile’s cult following.

“Our research has shown that what matters when it comes to delivering high-quality software on time and within budget is a robust requirements engineering process and having the psychological safety to discuss and solve problems when they emerge, whilst taking steps to prevent developer burnout.”

The Agile Manifesto has been criticized over the years. The infamous UK Post Office Horizon IT system was an early large-scale project to use the methodology, although blaming an Agile approach for the system’s design flaws seems a bit of a stretch.

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• IBM warns Global Tech Services staff that 346 UK heads will roll in latest redundancy action
• Erik Meijer: AGILE must be destroyed, once and for all

It is also easy to forget that other methodologies have their own flaws. Waterfall, for example, uses a succession of documented phases, of which coding is only a part. While simple to understand and manage, Waterfall can also be slow and costly, with changes challenging to implement.

Hence, there is a tendency for teams to look for alternatives.

Projects where engineers felt they had the freedom to discuss and address problems were 87 percent more likely to succeed. Worryingly, workers in the UK were 13 percent less likely to feel they could discuss problems than those in the US, according to the study.

Many sins of today’s tech world tend to be attributed to the Agile Manifesto. A neverending stream of patches indicates that quality might not be what it once was, and code turning up in an unfinished or ill-considered state have all been attributed to Agile practices.

One Agile developer criticized the daily stand-up element, describing it to The Register as “a feast of regurgitation.”

However, while the Agile Manifesto might have its problems, those stem more from its implementation rather than the principles themselves. “We don’t need a test team because we’re Agile” is a cost-saving abdication of responsibility.

In highlighting the need to understand the requirements before development begins, the research charts a path between Agile purists and Waterfall advocates.

Article link: https://www-theregister-com.cdn.ampproject.org/c/s/www.theregister.com/AMP/2024/06/05/agile_failure_rates/

We examined best practices from around the world to identify proven ways to implement e-health successfully. These insights could help other countries unlock their own e-health potential.

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Implementing new national e-health¹ solutions is inherently complex, and the challenges extend well beyond the technology domain. Facilitating adoption and regular use of e-health solutions by patients and healthcare professionals (HCPs) can prove especially fraught, yet widespread adoption is an important component of realizing the full potential of these solutions.

Expectations for e-health solutions can be high, with patients assuming their interactions with e-health solutions will mirror their digital shopping, banking, and takeout and delivery experiences when it comes to ease of use.² HCPs likely hope to streamline their processes and integrate solutions easily into their existing systems, but reality often diverges from this ideal³:

• Patients frequently find their e-health experiences are not intuitive for many reasons, including poor app design and patients’ lack of understanding of medical terminology.
• Workflows for e-health applications such as electronic health records (EHRs) and e-prescriptions are based on clinical processes rather than a user’s perspective.
• Data privacy and IT security protections, while necessary and important, can frustrate users’ attempts to log in to apps.
• The practical value of e-health solutions may be unclear to patients (and HCPs).
• HCPs may find e-health solutions difficult to integrate with their existing systems.

Despite these challenges, e-health solutions have demonstrated their potential to improve care quality, cost, and patient and HCP experience. 

Indeed, a McKinsey assessment shows that the potential value of fully utilizing 26 digital healthcare technologies in 14 countries is equal to 8 to 12 percent of total healthcare spending within each country.⁴ Of this estimated value, about 70 percent could be captured by hospitals and HCPs and 30 percent by health insurers. 

This article shares strategic actions that successfully spurred adoption and regular use of e-health solutions in countries around the world and lays out how other countries could combine and implement these strategic actions in three phases: setup, scale-up, and enhancing benefits. The analysis conducted for this article and real-world examples illustrate how these strategic actions, along with a holistic change-management program, could be used to scale e-health solutions in other countries and health systems.

Global e-health’s considerable potential

Digitalizing healthcare systems and implementing e-health solutions at the national level could make information more readily accessible and improve data sharing. Furthermore, using analytics-based e-healthcare solutions could improve treatments, avoid unnecessary interventions, and reduce medical and prescription errors. For example, clinicians could use their time during initial appointments more efficiently and avoid follow-up appointments with ready access to patient information. Easier intrahospital communications and reduced admissions enabled by remote monitoring could further boost efficiencies. And telemedicine, which facilitates timely treatment even for patients in remote and rural areas, could help close gaps in healthcare provisioning if combined with affordable, high-speed internet access.⁵

Governments and public institutions have been investing in e-health solutions for decades, prompted by the potential of these technologies. The United States launched one of the first EHR projects in the early 1970s,⁶ and in an early form of telemedicine, Norway relied on videoconferences for long-distance outpatient medical consultations and treatment in 1996.⁷ Since then, e-health solutions have been deployed around the world, with investments increasing markedly during the COVID-19 pandemic. In 2017, the size of the global e-health market⁸—including investments in e-health apps, devices, online pharmacies, and online consultations—was estimated at $19 billion; by 2022, it had grown to $64 billion.⁹ The market is projected to achieve a CAGR of 11.31 percent and reach $109 billion by 2027.¹⁰

According to McKinsey analysis, some investments in national e-health solutions are not yielding the desired adoption rates. In Germany, for example, less than 1.5 percent of patient records have been captured digitally since the country implemented its EHR system in 2021.¹¹ Further impeding adoption, of the 30 to 40 percent of HCPs that have installed EHR applications, only 2 to 3 percent use them.¹²

Although elegant user design can contribute to widespread adoption, our analysis of national e-health systems¹³ reveals that certain strategic actions to introduce technologies and encourage solution use are more likely to facilitate adoption and successful implementation.

Scaling solution adoption: Best practices in action

Countries around the globe have used various combinations of strategic actions to achieve widespread adoption and use of their national e-health solutions. There are numerous adoption-boosting actions that—when applied at the right time and in the right sequence—have yielded favorable results in the countries reviewed as part of this analysis; national e-health solutions take certain strategic actions most frequently (exhibit). 

Scaling national e-health: Best practices from around the world

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We examined best practices from around the world to identify proven ways to implement e-health successfully. These insights could help other countries unlock their own e-health potential.

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Implementing new national e-health¹ solutions is inherently complex, and the challenges extend well beyond the technology domain. Facilitating adoption and regular use of e-health solutions by patients and healthcare professionals (HCPs) can prove especially fraught, yet widespread adoption is an important component of realizing the full potential of these solutions.Share

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Expectations for e-health solutions can be high, with patients assuming their interactions with e-health solutions will mirror their digital shopping, banking, and takeout and delivery experiences when it comes to ease of use.² HCPs likely hope to streamline their processes and integrate solutions easily into their existing systems, but reality often diverges from this ideal³:

• Patients frequently find their e-health experiences are not intuitive for many reasons, including poor app design and patients’ lack of understanding of medical terminology.
• Workflows for e-health applications such as electronic health records (EHRs) and e-prescriptions are based on clinical processes rather than a user’s perspective.
• Data privacy and IT security protections, while necessary and important, can frustrate users’ attempts to log in to apps.
• The practical value of e-health solutions may be unclear to patients (and HCPs).
• HCPs may find e-health solutions difficult to integrate with their existing systems.

Despite these challenges, e-health solutions have demonstrated their potential to improve care quality, cost, and patient and HCP experience. 

Indeed, a McKinsey assessment shows that the potential value of fully utilizing 26 digital healthcare technologies in 14 countries is equal to 8 to 12 percent of total healthcare spending within each country.⁴ Of this estimated value, about 70 percent could be captured by hospitals and HCPs and 30 percent by health insurers. 

This article shares strategic actions that successfully spurred adoption and regular use of e-health solutions in countries around the world and lays out how other countries could combine and implement these strategic actions in three phases: setup, scale-up, and enhancing benefits. The analysis conducted for this article and real-world examples illustrate how these strategic actions, along with a holistic change-management program, could be used to scale e-health solutions in other countries and health systems.

Global e-health’s considerable potential

Digitalizing healthcare systems and implementing e-health solutions at the national level could make information more readily accessible and improve data sharing. Furthermore, using analytics-based e-healthcare solutions could improve treatments, avoid unnecessary interventions, and reduce medical and prescription errors. For example, clinicians could use their time during initial appointments more efficiently and avoid follow-up appointments with ready access to patient information. Easier intrahospital communications and reduced admissions enabled by remote monitoring could further boost efficiencies. And telemedicine, which facilitates timely treatment even for patients in remote and rural areas, could help close gaps in healthcare provisioning if combined with affordable, high-speed internet access.⁵

Governments and public institutions have been investing in e-health solutions for decades, prompted by the potential of these technologies. The United States launched one of the first EHR projects in the early 1970s,⁶ and in an early form of telemedicine, Norway relied on videoconferences for long-distance outpatient medical consultations and treatment in 1996.⁷ Since then, e-health solutions have been deployed around the world, with investments increasing markedly during the COVID-19 pandemic. In 2017, the size of the global e-health market⁸—including investments in e-health apps, devices, online pharmacies, and online consultations—was estimated at $19 billion; by 2022, it had grown to $64 billion.⁹ The market is projected to achieve a CAGR of 11.31 percent and reach $109 billion by 2027.¹⁰

According to McKinsey analysis, some investments in national e-health solutions are not yielding the desired adoption rates. In Germany, for example, less than 1.5 percent of patient records have been captured digitally since the country implemented its EHR system in 2021.¹¹ Further impeding adoption, of the 30 to 40 percent of HCPs that have installed EHR applications, only 2 to 3 percent use them.¹²

Although elegant user design can contribute to widespread adoption, our analysis of national e-health systems¹³ reveals that certain strategic actions to introduce technologies and encourage solution use are more likely to facilitate adoption and successful implementation.

Scaling solution adoption: Best practices in action

Countries around the globe have used various combinations of strategic actions to achieve widespread adoption and use of their national e-health solutions. There are numerous adoption-boosting actions that—when applied at the right time and in the right sequence—have yielded favorable results in the countries reviewed as part of this analysis; national e-health solutions take certain strategic actions most frequently (exhibit). 

Exhibit 

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These strategic actions for scaling e-health adoption can be grouped into three deployment phases: setup, scale-up, and enhancing benefits. The phases can be viewed as a continuous transition with a shifting focus rather than as a linear process in which phases are completed consecutively or in a specific order.

The analysis for this article shows that a systematic approach—implementing the right actions at the right time—helps navigate the phases of scaling adoption and usage. Establishing overarching change and communication plans at the outset is an important contributor to adoption. Once a plan is in place, a potentially effective set of strategic actions could be selected and tailored to the e-health solution and the specific needs of the targeted users.

Setup phase: Attracting users

The primary objective of the setup phase is to attract a critical mass of patients and HCPs to new e-health solutions. Supporting strategic actions demonstrate to users how a new e-health solution addresses a specific problem, and they clearly state the solution’s benefits. Additionally, regulatory measures could be explored along with other actions to lower barriers to entry, such as establishing trust in e-health solutions and streamlining registration to simplify solution onboarding for patients and HCPs. Furthermore, compelling incentives such as financial compensation or reimbursements can be evaluated to determine their potential for encouraging proper usage.

These questions could help leaders focus efforts during the setup phase:

• What is the best use case to begin with, for patients and HCPs?
• Could regulatory measures be evaluated to ascertain their potential impact on achieving adoption?
• What actions could help cultivate trust?
• How can solutions be integrated smoothly with existing IT systems while ensuring interoperability?

Compelling use cases.Compelling use cases convey how a new e-health solution addresses an unmet need for patients or HCPs and show that the solution is easy to use and adds real value in practice. Simple dimensions to assess the potential of new e-health use cases are the number of users (patients and HCPs) affected, transaction volumes, and the potential impact of the e-health solution per transaction.

During the COVID-19 pandemic, some use cases demonstrated effective ways to attract new and lapsed users to e-health solutions and help scale those solutions. The benefits of the COVID-19-related solutions were clearly communicated, and the solutions were easy to use and encouraged frequent use (for example, to show proof of vaccination or COVID-19 test results multiple times daily). Consequently, the solutions attracted many users.

Use of Austria’s e-health system rose during the COVID-19 pandemic. The country introduced an electronic vaccination record in 2020 as a new feature of ELGA, its national electronic patient record system. In addition, free COVID-19 antigen tests in drugstores were available only via ELGA’s e-medication function. These strategic actions helped to further strengthen the system’s value proposition and encouraged the reactivation of a sizable number of ELGA user accounts.¹⁴

Management of adoption, use, privacy, and security. Some measures may help encourage proper adoption of e-health solutions on a national level. McKinsey research indicates that both clearly defined consent management policies and measures that mandate high data privacy and cybersecurity standards could potentially cultivate user trust in e-health solutions (a prerequisite for scaling new use cases). Other measures that could help facilitate adoption could also be explored, such as requiring adoption by HCPs or requiring users to actively opt out of digital systems versus actively sign up for them. However, such measures can also have unintended consequences, especially if they lack good design. Further, ensuring compliance with a complex web of regulations requires investment in legal, security, and compliance functions, which can make entering the market challenging for small health systems and innovators.

In Denmark, patient health data is automatically integrated in the national health portal, sundhed.dk. The government system, which contains each resident’s health status, medical history, prescriptions, and other relevant health information, is now mandatory for all HCPs in the country, and patients may not opt out of it. Notably, the system is highly transparent about how patients’ data is used, and strict rules and regulations limit access to and use of the EHR system to authorized HCPs for legitimate medical purposes.¹⁵ Patients can also access an activity log for their EHR that displays all data requests from HCPs.¹⁶ In addition to other levers, the combination of regulatory measures and other strategic actions increased the number of frequent users of sundhed.dk to about 45 percent of the Danish population by around 2010.¹⁷

Denmark also offered incentives for HCPs, gradually building HCP adoption of e-health solutions. For example, physicians received €1,500 per year to spend on e-health and were reimbursed more quickly if they were connected to the national healthcare infrastructure. Eventually Denmark mandated that EHRs integrate with the national e-health infrastructure. Once that legal requirement was established, 100 percent of HCPs adopted the national system.¹⁸

Interoperability and integration.A lack of integration and interoperability of IT systems can be one of the biggest barriers to scaling new e-health solutions. The IT systems for different stakeholders (general practitioners, hospitals, national databases, and so on) are generally heterogeneous—not connected or standardized in terms of their data or interfaces. Designing e-health solutions and supporting technical capabilities to make integrating them with existing IT systems as simple as possible fosters adoption among HCPs. Terminology services are one example of technical capabilities to ensure data interoperability. These services act as intermediaries, effectively mapping different coding and exchange standards to enable seamless communication. Financial incentives to reduce the burden for HCPs and offset initial investment costs can also be considered. 

Iceland partnered with the vendors that created Saga, the country’s e-healthcare system, to automate the integration of that system with individual HCPs’ existing IT systems.¹⁹ This integration allowed HCPs to access the patient information in Saga directly from their own systems, eliminating the need to switch between different applications or manually enter data. Today, the EHR is used by more than 90 percent of HCPs in Iceland.²⁰

Scale-up phase: Fostering frequent usage

Once a critical mass of users has been reached, strategic actions in the scale-up phase center on encouraging users to become active, frequent users of e-health solutions. The quality of customers’ early experience with e-health solutions often determines whether they make using them a habit. Use rates can also be increased by effectively integrating different solutions—boosting usage across all solutions—as well as by further optimizing user experience, which enhances the value proposition of the solution.

These questions could help leaders focus efforts during the scale-up phase:

• What is the best approach to making the e-health solution part of users’ daily routines?
• Is the solution design user-centric?
• Which use cases can boost regular usage?

Solution integration. The integration of different e-health solutions provides the dual benefits of improving user experiences and boosting the usage rates for all connected solutions. Patients prefer a simple, consistent e-health experience with uninterrupted user journeys. ²¹Thus, making it easier and more convenient to transition from one solution to another increases the likelihood that users will engage with all solutions more often. When facilitated by use of a central identity, central access, and consent management solutions, integrated e-health solutions help create this holistic patient experience.

Singpass, Singapore’s national management system for verifying citizens’ identities, is an important enabler for integrating various e-health solutions. Singpass is subject to regular, rigorous review and was introduced as part of a much larger identity verification initiative—Singapore’s mandated use of facial recognition—and privacy framework.²² Singpass allows users to easily share data between apps, and (with users’ consent) apps can obtain information from Singpass to verify users’ identity.²³ During the COVID-19 pandemic, citizens were required to submit health declarations online. Singpass enabled the integration of data from these declarations with other systems, such as immigration records and COVID-19 testing results. This helped authorities in Singapore identify potential cases of COVID-19 and greatly aided contact tracing.²⁴ Singpass was also used to incorporate vaccination records from various sources—including hospitals, clinics, and vaccination centers—into a centralized system, allowing citizens to access their vaccination records online and authorities to track vaccination coverage.

User centricity. Across industries, digitalization has proved to be most beneficial when it is highly focused on end users.²⁵ When new e-health solutions are designed and developed with insufficient focus on user centricity, poor user experience and limited value in practice often result. This drives down use rates for e-health solutions and impedes scaling. End users of e-health solutions represent a range of populations, including patients, medical professionals, and pharmacies. Patient-focused solutions involve patient journeys and integrating those different journeys wherever possible.

Solutions focused on HCPs, on the other hand, emphasize easy incorporation into daily processes and seamless integration into IT systems. Involving a broad range of stakeholders in the development process for e-health solutions can be invaluable in helping facilitate user centricity across stakeholders. Involvement can vary widely, including conducting research to understand preferences of different user groups; bringing together user group stakeholders to generate ideas, codesign solutions, and provide feedback on prototypes; and conducting user testing that evaluates the usability, feasibility, and acceptability of e-health solutions.

Via the Kanta Services platform, Finnish citizens can access their health data and prescriptions, HCPs can access EHRs and write prescriptions, and pharmacies can access a comprehensive pharmaceutical database, among other capabilities. The platform’s development involved patients, healthcare professionals, and IT experts, and it focused on making the platform user-friendly, secure, and practical for daily use. Consequently, Finland was able to streamline physicians’ workflow and ease their administrative burden by integrating access to services into a single platform.²⁶Prior to Kanta Services, patients could not access their own records, and it was not uncommon for physicians to have difficulty accessing patient records from other units; physicians would need to log in and out of multiple systems throughout the day to access records as well as perform daily tasks such as viewing medical images and ordering laboratory tests.²⁷

High-volume use cases. Digital healthcare applications with high transaction volumes, such as e-prescriptions, could help to further drive adoption at scale of other solutions. Integrating these high-transaction-volume solutions with other e-health solutions fosters greater engagement and increased use across solutions.

Since the introduction of e-prescriptions in Estonia and the integration of prescription data into the country’s EHR system in 2010, the country has seen a substantial increase in the use of both solutions. Today, nearly 100 percent of prescriptions issued in Estonia are digital, and 99 percent of all healthcare data has been captured in the EHR system. Patients can access a full overview of their medications and a data log for each prescription via the patient portal. Additionally, a drug interaction alert service checks e-prescription data for medical interactions and displays notifications to HCPs to alert them to any potential concerns. Today, all Estonian physicians use the drug alert service as part of their daily routines.²⁸

Enhancing benefits: Encouraging further usage and enabling ecosystem growth 

Once a critical mass of users is frequently using e-health solutions or an entire ecosystem of solutions, a variety of innovative strategic actions can help maximize the benefits of the digital ecosystem. Developing new partnerships with HCPs and organizations, for example, may expand the range of services that are available via the e-health solution and add value for users. By consistently delivering value-adding offerings, the e-health ecosystem could deepen user engagement and foster loyalty, increasing adoption and use of the solution and ultimately leading to the realization of greater overall value. 

These questions could help leaders focus efforts during the enhancing-benefits phase:

• How can e-health adoption lead to valuable innovations and insights?
• What is the key to creating a thriving e-health ecosystem and using data effectively?
• How can the full potential of e-health solutions be unlocked?

Data-driven innovations. A central national e-health infrastructure, especially a national data hub, may improve data standards as well as quality, availability, and accessibility of data. These improvements could, in turn, create opportunities for data-driven, value-adding analytics solutions from third parties.

Israel’s national database, the National Health Information Exchange (NHIE), contains health data from various sources—such as hospitals, clinics, and health insurers—and is managed by the Israeli Ministry of Health (IMH). While the NHIE is not publicly available, approved researchers, start-ups, and organizations can access and share the data at no cost with permission from the IMH. To ensure the privacy and security of the data, access to the NHIE is tightly regulated, and users must adhere to strict guidelines and regulations.²⁹ One start-up that has leveraged Israel’s NHIE uses AI-powered medical-scan readers to detect early signs of cancer. The software is designed to analyze medical images such as computerized tomography (CT) scans and X-rays and identify potential anomalies that could indicate the presence of cancer or other diseases. By accessing Israel’s population health data, the solution can train its algorithms on a large and diverse data set, improving the accuracy and reliability of its scans.

A rich ecosystem. Opening a national e-health infrastructure to third parties helped to scale adoption and add value in some of the countries included in the analysis conducted for this article. Indeed, third-party solutions could help accelerate innovation and access to additional value pools. Implementing robust protections for personal health information and ensuring respect for patients’ rights before opening e-health infrastructure to third parties can foster trust in the system. 

As discussed above, Israel’s NHIE allows health organizations as well as start-ups to not only access available health data but also easily connect to the e-health infrastructure using uniform interoperability standards. This standardization helps promote competition and innovation by lowering barriers to entry for companies new to the market. An open API–based platform allows third-party developers to build services that can easily connect to it. Collaboration and innovation are also enabled by this openness, which makes the platform’s data and services available for the development of new solutions. The data-sharing agreements Israel has established govern the secure and controlled sharing of its health data, allowing that data to be used to improve health outcomes while safeguarding patient privacy. A broader ecosystem was thus created via an open digital infrastructure that facilitated competition among healthcare players.³⁰

Population health management and informed decisions and policy making. Digitalized healthcare data could be used for central analytics such as population health management. This data could aid understanding of the overall health and care needs of a population as well as the availability of healthcare within a system, possibly improving care coordination and resource allocation.

Chicago’s Smart Data Project showcases how predictive analytics can support effective public health initiatives. The Chicago Department of Public Health employs predictive models that identify households at high risk for lead poisoning and monitor food establishments to detect safety violations. Using publicly available data, these models enable proactive interventions to help protect public health.³¹

A tailored approach to encouraging adoption at scale: Fundamental steps

The adoption of e-health solutions cannot be approached with a one-size-fits-all mindset. It is important to recognize that the diverse nature of healthcare systems, technological infrastructures, cultural contexts, and regulatory environments necessitates tailored approaches for each setting. What may work seamlessly in one country may encounter considerable challenges or inefficiencies in another.

The strategic actions provided in this article are instructive, offering insights into successful approaches to achieving e-health solution adoption at scale. They should not be regarded as rigid templates but rather flexible blueprints that can be customized and optimized to a country’s specific circumstances. These actions can serve as guideposts as leaders engage in three potential preliminary steps to develop a customized approach to scaling e-health solutions: defining baselines, developing a target design, and creating a detailed action plan.

Defining baselines

When successfully implemented, tailored e-health solutions typically begin with a clear understanding of a country or region’s baseline for three critical factors: the digital affinity of user groups, the requirements of local healthcare systems, and the digital maturity of infrastructure. 

Assessing user groups’ digital affinity entails understanding their familiarity and comfort with technology. This helps identify potential barriers that may affect adoption and enables targeted interventions to increase acceptance. Local healthcare system requirements could be evaluated by analyzing existing structures, policies, and processes to ensure solutions align with the context and integrate effectively. And analyzing technical capabilities, interoperability, and data standards of existing infrastructure provides insight into its digital maturity. This assessment can determine the feasibility of deploying solutions and identify necessary upgrades for successful implementation and scalability.

Developing a target design

Thoughtful analysis of solutions that would be most beneficial as well as consideration of target user groups and stakeholders can facilitate an effective target design for an adoption strategy. This process involves strategic design choices, including determining the optimal sequencing of solution rollout and ensuring seamless interconnection and interoperability among different offerings. The target design provides a comprehensive vision for structuring solutions and their interactions within the broader e-health ecosystem.

Creating a detailed action plan

Achieving scalability in e-health solutions necessitates an action plan that extends beyond individual solutions and encompasses the entire ecosystem of e-health offerings. Identifying the strategic actions that yield the greatest impact for each specific solution, as well as those that influence the overall offering, is central to effectively scaling adoption. This understanding can inform the appropriate timing and sequencing of actions, which support optimal implementation and adoption. Above all, change management is an integral component of any action plan because it plays a pivotal role in bolstering acceptance and adoption among stakeholders from the outset.

An action plan in action.The Qatar Ministry of Public Health developed a comprehensive action plan to establish its e-health ecosystem.³² The ecosystem’s foundation is a central platform that provides a national health information exchange and a repository that facilitates the secure exchange and storage of health information. The platform will enable communication between public and private healthcare players, including hospitals, health centers, clinics, and pharmacies, and will support patient empowerment.

As part of the program, the ministry will launch multiple solutions, including a health information viewer for clinicians, a national e-prescription system, national disease registries and management, traditional AI capabilities, and a patient-centric mobile app.

The ministry started implementing a strategy built on adoption propelled by target segments and change management strategy; this strategy comprised multiple steps to help ensure adoption and wide use across all national solutions, including the following:

• implementing a user-centric design approach involving a wide group of end users (clinicians, patients, and technology experts)
• implementing an easy-to-use patient consent system integrated with the patient application and the health information viewer
• ensuring solution capabilities to streamline adoption, including embedding solutions into clinical workflows
• planning multiple training initiatives—for example, training programs tailored to solutions and healthcare systems
• implementing a communication plan that regularly engages all stakeholders

As the analysis conducted for this article demonstrates, customization, adaptability, and localized approaches in scaling e-health solutions are of utmost importance. Indeed, embracing this mindset and leveraging the wealth of proven strategic actions available can accelerate the adoption of e-health solutions. And, more broadly, tailoring solutions and strategies to meet patients and HCPs where they are advances e-health’s immense potential to enhance healthcare delivery and improve patient outcomes on a global scale.

ABOUT THE AUTHOR(S)

Ali Ustun is a partner in McKinsey’s Doha office, where Osman Ozturk is an associate partner; Florian Niedermann is a senior partner in the Stuttgart office; Matthias Redlich is a partner in the Frankfurt office, where Katharina Sickmüller is an associate partner; Panco Georgiev is a senior partner in the Dubai office, and Andreas Faber is an associate partner in the Cologne office.

Article link: https://www.mckinsey.com/industries/healthcare/our-insights/scaling-national-e-health-best-practices-from-around-the-world

The U.S. national security community faces a rise in global threats and a rapidly changing technological environment that offers both challenges and opportunities for the future fight. Adversaries and competitors are contesting the United States’ traditional edge in innovation, agility, global power projection, and ability to shape the strategic environment. To stay competitive, the United States must be able to engage with industry, harness technological advances, and field new capabilities with unaccustomed speed and flexibility—and to do so within ever-tightening budget constraints.

The U.S. Department of Defense’s (DoD’s) Planning, Programming, Budgeting, and Execution (PPBE) System was originally developed in the 1960s as a structured approach for planning long-term resource development, assessing program cost-effectiveness, and aligning resources to strategies. Yet changes to the strategic environment, the industrial base, and the nature of military capabilities have raised the question of whether existing U.S. defense budgeting processes remain well aligned with national security needs.

In response, Congress called for the establishment of the Commission on PPBE Reform. As part of its data collection efforts, the commission asked RAND researchers to conduct case studies of budgeting processes across nine comparative organizations: five international defense organizations and four U.S. federal government agencies. Congress also specifically requested two case studies of near-peer competitors, and the research team selected the other seven cases in close partnership with the commission. This site collects the findings from the RAND project in three volumes, plus an executive summary.

RAND’s Findings on PPBE Reform

• Planning, Programming, Budgeting, and Execution in Comparative Organizations: Volume 1, Case Studies of China and Russia
• Planning, Programming, Budgeting, and Execution in Comparative Organizations: Volume 2, Case Studies of Selected Allied and Partner Nations
• Planning, Programming, Budgeting, and Execution in Comparative Organizations: Volume 3, Case Studies of Selected Non-DoD Federal Agencies
• Planning, Programming, Budgeting, and Execution in Comparative Organizations: Volume 4, Executive Summary
• PPlanning, Programming, Budgeting, and Execution in Comparative Organizations: Volume 5, Additional Case Studies of Selected Allied and Partner Nations
• Planning, Programming, Budgeting, and Execution in Comparative Organizations: Volume 6, Additional Case Studies of Selected Non-DoD Federal Agencies
• Planning, Programming, Budgeting, and Execution in Comparative Organizations: Volume 7, Executive Summary for Additional Case Studies

In Their Own Words

• Reforming DoD’s Planning, Programming, Budgeting, and Execution Process for a Competitive FutureCongress, the Department of Defense, and other key stakeholders are working on once-in-a-generation changes to the planning, programming, budgeting, and execution (PPBE) process to foster greater speed, agility, and innovation. Watch guests, including former secretary of defense Chuck Hagel and chair of the PPBE Reform Commission Bob Hale, discuss PPBE reform during this video from a recent RAND event.Feb 8, 2024

Article link: https://www.rand.org/nsrd/projects/PPBE-reform.html?

By JOHN BREEDEN IIMAY 14, 2024

Recent studies have started to show that there are serious downsides when it comes to such programs’ ability to produce secure code.

It’s no secret that artificial intelligence is almost everywhere these days. And while some groups are worried about potentially devastating consequences if the technology continues to advance too quickly, most government agencies are pretty comfortable adopting AI for more practical purposes, employing it in ways that can help advance agency missions.

And the federal government has plenty of guidelines in place for using AI. For example, the AI Accountability Frameworkfor Federal Agencies provides guidance for agencies that are building, selecting or implementing AI systems. According to GAO and the educational institutions that helped to draft the framework, the most responsible uses of AI in government should be centered around four complimentary principals. They include governance, data, performance and monitoring.

Writing computer code, or monitoring code written by humans to look for vulnerabilities, fits within that framework. And it’s also a core capability that most of the new generative AIs easily demonstrate. For example, when the most popular generative AI program, ChatGPT, upgraded to version 4.0, one of the first things that developer OpenAI did at the unveiling was to have the AI write the code to quickly generate a live webpage.

Given how quickly most generative AIs can code, it’s little wonder that according to a recent survey by GitHub, more than 90% of developers are already using AI coding tools to help speed up their work. That means that the underlying code for most applications and programs being created today is at least partially made by AI, and that includes code that is both written or used by government agencies. However, while the quick pace that AI is able to generate code is impressive, recent studies have started to show that there are serious downsides that come along with that speed, especially when it comes to security.

Trouble in AI coding paradise

The new generative AIs have only been successfully coding for, at most, a couple of years depending on the model. So, it’s little wonder that evaluations of their coding prowess are slow to catch up. But studies are being conducted, and the results don’t bode well for the future of AI coding, especially for mission critical areas within government, at least without some serious improvements.

While AIs are generally able to quickly create apps and programs that work, many of those AI-created applications are also riddled with cybersecurity vulnerabilities that could equate to huge problems if dropped into a live environment. For example, in a recent study conducted by the University of Quebec, researchers asked ChatGPT to generate 21 different programs and applications in a variety of programming languages. While every single one of the created applications the AI coded worked as intended, only five of them were secure from a cybersecurity standpoint. The rest had dangerous vulnerabilities that attackers could easily use to compromise anyone who deployed them. 

And these were not minor security flaws either. They included almost every single vulnerability listed by the Open Web Application Security Project, and many others.

In an effort to find out why AI coding was so dangerous from a cybersecurity standpoint, researchers at the University of Maryland, UC Berkeley and Google decided to switch things up a bit and task generative AI not with writing code, but with examining already assembled programs and applications to look for vulnerabilities. That study used 11 AI models, which were each fed hundreds of examples of programs in multiple languages. Applications rife with known vulnerabilities were mixed in with other code examples which were certified as secure by human security experts.

The results of that study were really bad for the AIs. Not only did they fail to detect hidden vulnerabilities, with some AIs missing over 50% of them, but most also flagged secure code as being vulnerable when it was not, leading to a high rate of false positives. It seems that those dismal results even surprised the researchers, who decided to try and correct the problem by training the AIs in better vulnerability detection. They fed the generative AIs thousands of examples of both secure and insecure code, along with explanations whenever a vulnerability was introduced.

Surprisingly, that intense training did little to improve AI performance. Even when expanding the large language models the AIs used to look for vulnerable code, the final results were still unacceptably bad both in terms of false positives and letting vulnerabilities slip through undetected. That led the researchers to conclude that no matter how much they tweaked the models, that the current generation of AI and “deep learning is still not ready for vulnerability detection.” 

Why is AI so bad at secure coding?

All of the surveys referenced here are relatively new, so there is not a lot of explanation yet as to why generative AI, which performs well at so many tasks, would be so bad when it comes to spotting vulnerabilities or writing secure code. The experts that I talked with said the most likely reason is that generative AIs are trained on thousands or even millions of examples of code written by humans that come from open sources, code libraries and other repositories, and much of that is heavily flawed. Generative AI may simply be too poisoned by all those bad examples used in its training to redeem. Even when researchers from the University of Maryland and UC Berkeley study tried to correct the models with fresh data, their new examples were just a drop in the bucket, and not nearly enough to improve performance.

One study conducted by Secure Code Warrior did try and address this question directly with an experiment that selectively fed generative AIs specific examples of both vulnerable and secure code, tasking them with identifying any security threats. In the case of that study, the difference between the secure and vulnerable code examples presented to the AIs were very subtle, which helped researchers determine what factors were specifically tripping up the AIs when it came to vulnerability detection in code.

According to SCW, one of the biggest reasons that generative AIs struggle with secure coding is a lack of contextual understanding about how the code in question fits in with larger projects or the overall infrastructure, and all of the subsequent security issues that can stem directly from that. They give several examples to prove this point, where a snippet of code should be considered secure if it is being used to trigger a standalone function but then becomes vulnerable with business logic flaws, improper permissions or security misconfigurations when integrated into a larger system or project. Since the generative AIs don’t generally understand the context of how code they are examining is being used, it will often flag secure code as vulnerable or code that has vulnerabilities as safe. 

In a sense, because an AI does not know the context of how code will be used, it sometimes ends up guessing about its vulnerability status, since AIs almost never admit that they don’t know something. The other area that AIs struggled with in the SCW study was when a vulnerability came down to something small, like the order of various input parameters. Generative AIs may simply not be experienced enough to know how something small like the order of input parameters in the middle of a large snippet of code can lead to security problems.

The study does not offer up a solution for fixing an AI’s inability to spot insecure code, but does say that generative AI could still have a role in coding, but only when paired tightly with experienced human developers who can keep a watchful eye on their AI companions. For now, without a good technical solution, that may be the best path forward for agencies that need to tap into the speed that generative AI can offer when coding, but can’t accept the risks that come along with unsupervised AI acting independently when creating government applications and programs.

John Breeden II is an award-winning journalist and reviewer with over 20 years of experience covering technology. He is the CEO of the Tech Writers Bureau, a group that creates technological thought leadership content for organizations of all sizes. Twitter: @LabGuys

Article link: https://www.nextgov.com/artificial-intelligence/2024/05/feds-beware-new-studies-demonstrate-key-ai-shortcomings/396526/?

GETTYIMAGES.COM / ANDREY SUSLOV

By ROSS WILKERSMAY 28

The Army calls out specific modern practices it wants to incorporate and asks industry about others that could work here too.

The Army has started to develop a new software development support services contract with a touted ceiling value north of $1 billion over 10 years.

A new sources sought notice describes the New Modern Software Development IDIQ as a means to hire a group of contractors that can perform the work on rapidly-awarded task orders as they come.

At this juncture, the Army plans to choose up to 10 companies in total that include those reserved for small businesses.

The Army also envisions holding an on-ramp process to bring more contractors into the fold, along with the potential of off-ramps to move away from those with high rates of unsuccessful task order proposals or no bids.

Customization is a key element of the requirements, whether that be in the development of a new product or the modification of a current offering. Awardees will also be responsible for enabling software-as-a-service hosting and security.

The Army is emphasizing modern software development practices that include DevSecOps, Agile, lean and continuous integration/continuous delivery.

At the same time, the Army’s list of questions in the request for information also asks about other areas of software development it should include in the contract.

A second key question worth highlighting is whether interested parties can provide examples or recommendations of how to use experience in coding challenges to establish employee qualifications. The Army sees that approach as a potential alternative to certifications and proposals, depending on the answers, of course.

Significant question number three to call out zeroes in on the two-phase evaluation approach the Army is mulling for this requirement.

For phase two, the Army is considering technology challenges versus demonstrations as the focus there. The Army wants to know what respondents think about that.

Responses to the RFI are due June 10.

Article link: https://washingtontechnology.com/contracts/2024/05/army-lifts-curtains-planned-1b-software-development-contract/396919/?

Mike BrownContributor

Michael Brown is a partner at the VC firm Shield Capital.

Almost a decade ago, Secretary of Defense Ash Carter came to Stanford University in 2015 to announce a bridge between Silicon Valley and the Pentagon, a new organization he termed the Defense Innovation Unit Experimental or DIUx. Secretary Carter realized earlier than many of the technologies the military needed would come from commercial companies at the forefront of AI, autonomy, cyber and commercial space—not from government labs or defense primes.

Why? The Defense Department provides a much smaller proportion of global R&D than in the past (as other countries invested) and commercial businesses now invest more R&D dollars than the government. Sixty years ago, the Defense Department represented 36% of global R&D vs. 3% today. The five largest tech companies spend more than 10x on R&D in comparison to what the five largest defense primes spend.

Inauspicious Beginnings

Changing how the Department views and incorporates commercial technology has not been easy. DIU was initially conceived as a defense embassy to Silicon Valley. What became apparent was that Silicon Valley was not interested in an embassy but instead wanted opportunities to compete for defense contracts. In the fail-fast mode of Silicon Valley, Secretary Carter restarted the operation with a Silicon Valley entrepreneur and F-16 pilot, Raj Shah. Raj had the insight that DIU should be a front door to Pentagon projects which offered revenue contracts for companies that could solve military problems. His team pioneered the use of a fast-track acquisition authority and a competitive process that mirrored how most companies do sourcing.

However, there was a struggle getting Congress to approve and sustain a budget for this startup organization of about $30 million in 2017, and another hiccup when DIU’s reporting relationship changed from the Secretary to an Undersecretary whose primary focus was defense-developed technology—not commercial technology. I succeeded Raj as DIU director in 2018. Despite inconsistent support from defense leadership for budget and manpower, DIU gained approval for its own contracting capability and subsequently scaled to add 100 new vendors who, in turn, attracted 10-20x in venture capital for every $1 awarded in a DIU prototype contract. DIU also increased its transition rate for production contracts to 50% of every prototype effort begun, which in turn attracted 43 potential suppliers for every prototyping effort. Some of the companies now most associated with defense tech like Anduril, C3.ai, Rhombus Power, Shield AI and Vannevar Labs all got a start with DIU prototype contracts but have gone on to develop much more significant businesses serving the Defense Department.

Commercial Technology In The DoD Today

The Defense Department has again realized that accelerating the incorporation of disruptive technology is most effective when reporting to the Secretary of Defense. The Department is now applying commercial technology to its most important problems, specifically, what the military commands of the Indo-Pacific and Europe face in deterring China and Russia. Now with nearly $1 billion from Congress, DIU can field new capabilities in one to two years to support those military commands without waiting for multi-year budget alignment or traditional acquisition processes which on average field new capabilities in 17 years.

In addition, venture capital has begun to support defense tech in an unprecedented way. New firms like ours, Shield Capital, have formed to support national security applications while more established venture firms like Andreesen Horowitz, Lightspeed, and Bessemer Ventures have developed practices focused on defense within their firms. In aggregate, investment in defense tech is up 5x in the past six years and now represents $40 billion annually. With a larger amount of DoD’s budget focused on commercial tech, this is a win-win for the nation—new paths for businesses to ramp revenues faster while modernizing capabilities for the warfighter.

A New Age Bridge From The Pentagon To Silicon Valley

The early days of DIU began to attract the best and brightest of the Valley through contracts, but now with increased resources, there can be a much stronger flywheel effect when more companies receive larger production contracts and, in turn, the companies invest more in their defense product lines and production capacity. Expanding the defense industrial base is critical to any future war effort since the base has consolidated to such a degree that it would be severely constrained in wartime as production constraints in supplying Ukraine have highlighted. As more dollars flow to commercial companies, investors will back more entrepreneurs creating solutions for warfighters. A virtuous circle forms when the defense industrial base grows, is more competitive, offers more choice for the Department in terms of cost/performance and warfighters gain access to leading technology. For too long, our soldiers, sailors and airmen have had access to more modern technology in their civilian consumer lives than while in uniform.

Change is hard and it has taken dedicated civilians, investors, men and women in uniform as well as Congressional leaders years to realize the opportunity and momentum in leveraging commercial technology for defense applications. There is an opportunity at this inflection point to provide the nation and our allies a hedge that can complement the exquisite defense platforms today such as the F-35 and Columbia-class subs.

Today, DIU has the reporting relationship and widespread support to provide the best of what Silicon Valley can offer to equip our warfighters. In August 2023, Deputy Secretary of Defense Kathleen Hicks announced that DIU would be a focal point of the Replicator initiative with the aim of delivering thousands of autonomous, low-cost drones to the Indo-Pacific Command within 18-24 months. There appears to be progress 8 months in with an announcement this week that “the delivery of Replicator systems to the warfighter began earlier this month.”

Today, DIU has the reporting relationship and widespread support to provide the best of what Silicon Valley can offer to equip our warfighters. In August 2023, Deputy Secretary of Defense Kathleen Hicks announced that DIU would be a focal point of the Replicator initiative with the aim of delivering thousands of autonomous, low-cost drones to the Indo-Pacific Command within 18-24 months. There appears to be progress 8 months in with an announcement this week that “the delivery of Replicator systems to the warfighter began earlier this month.”

Article link: https://www.forbes.com/sites/mikebrown/2024/05/25/defense-innovation-inflection-point/?

Here’s why it Matters

So little is known about what’s happening in artificial intelligence and what might lie ahead. An international body could help fix that, experts argue. 

Across the globe, there is growing awareness of the risks of unchecked artificial intelligence research and development. Governments are moving fast in an attempt to address this, using existing legal frameworks or introducing new standards and assurance mechanisms. Recently, the White House proposed an AI Bill of Rights.

But the great paradox of a field founded on data is that so little is known about what’s happening in AI, and what might lie ahead.

This is why we believe the time is right for the creation of a global AI observatory — a GAIO — to better identify risks, opportunities, and developments and to predict AI’s possible global effects.

The world already has a model in the Intergovernmental Panel on Climate Change. Established in 1988 by the United Nations with member countries from around the world, the IPCC provides governments with scientific information they can use to develop climate policies. A comparable body for AI would provide a reliable basis of data, models, and interpretation to guide policy and broader decision-making about AI.

At present, numerous bodies collect valuable AI-related metrics. Nation-states track developments within their borders; private enterprises gather relevant industry data; and organizations like the OECD’s AI Policy Observatory focus on national AI policies and trends. While these initiatives are a crucial beginning, much about AI remains opaque, often deliberately. It is impossible to regulate what governments don’t understand. A GAIO could fill this gap through four main areas of activity.

It is impossible to regulate what governments don’t understand. A GAIO could fill this gap.

Thomas Malone et al. Advocates for a global AI observatory

1. Create a global, standardized incident-reporting databaseconcentrating on critical interactions between AI systems and the real world. For example, in the domain of biorisk, where AI could aid in creating dangerous pathogens, a structured framework for documenting incidents related to such risks could help mitigate threats. A centralized database would record essential details about specific incidents involving AI applications and their consequences in diverse settings — examining factors such as the system’s purpose, use cases, and metadata about training and evaluation processes. Standardized incident reports could enable cross-border coordination.

2. Assemble a registry of crucial AI systems focused on AI applications with the largest social and economic impacts, as measured by the number of people affected, the person-hours of interaction, and the stakes of their effects, to track their potential consequences.

3. Bring together global knowledge about the impacts of AI on critical areas such as labor markets, education, media, and health care. Subgroups could orchestrate the gathering, interpretation, and forecasting of data. A GAIO would also include metrics for both positive and negative impacts of AI, such as the economic value created by AI products and the impact of AI-enabled social media on mental health and political polarization.

4. Orchestrate global debate through an annual report on the state of AIthat analyzes key issues, patterns that arise, and choices governments and international organizations need to consider. This would involve rolling out a program of predictions and scenarios focused primarily on technologies likely to go live in the succeeding two to three years. The program could build on existing efforts, such as the AI Index produced by Stanford University.

A focus on facts rather than prescriptions

A GAIO would also need to innovate. Crucially, it would use collective intelligence methods to bring together inputs from thousands of scientists and citizens, which is essential in tracking emergent capabilities in a fast-moving and complex field. In addition, a GAIO would introduce whistleblowing mechanisms similar to the U.S. government’s incentives for employees to report on harmful or illegal actions.

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To succeed, a GAIO would need a comparable legitimacy to the IPCC. This can be achieved through its members including governments, scientific bodies, and universities, among others, and by ensuring a sharp focus on facts and analysis more than prescription, which would be left in the hands of governments.

Contributors to the work of a GAIO would be selected, as with the IPCC, on the basis of nominations by member organizations, to ensure depth of expertise, disciplinary diversity, and global representativeness. Their selection would also require maximum transparency, to minimize both real and perceived conflicts of interest.

The AI community and businesses using AI tend to be suspicious of government involvement, often viewing it as a purveyor of restrictions. But the age of self-governance is now over. We propose an organization that exists in part for governments, but with the primary work undertaken by scientists. All international initiatives related to AI would be welcomed.

In order to grow, a GAIO will need to convince key players from the U.S., China, the U.K., the European Union, and India, among others, that it will fill a vital gap. The fundamental case for its creation is that no country will benefit from out-of-control AI, just as no country benefits from out-of-control pathogens.

The greatest risk now is multiple unconnected efforts. Unmanaged artificial intelligence threatens important infrastructure and the information space we all need to think, act, and thrive. Before nation-states squeeze radically new technologies into old legal and policy boxes, the creation of a GAIO is the most feasible step.

This article is written by Sir Geoff Mulgan, a professor of collective intelligence, public policy, and social innovation at University College London;Thomas Malone, a professor of information management at MIT Sloan and the director of the MIT Center for Collective Intelligence; Divya Siddharth and Saffron Huang of the Collective Intelligence Project; Joshua Tanof the Metagovernance Project; and Lewis Hammond of the Cooperative AI Foundation.

Article link: https://mitsloan.mit.edu/ideas-made-to-matter/world-needs-a-global-ai-observatory-heres-why?

MAY 7, 2024

MITRE Federal AI Sandbox to be Powered by NVIDIA DGX SuperPOD 

McLean, Va., May 7, 2024 – MITRE is building a new capability intended to give its artificial intelligence (AI) researchers and developers access to a massive increase in computing power. The new capability, MITRE Federal AI Sandbox, will provide better experimentation of next generation AI-enabled applications for the federal government. The Federal AI Sandbox is expected to be operational by year’s end and will be powered by an NVIDIA DGX SuperPOD™ that enables accelerated infrastructure scale and performance for AI enterprise work and machine learning.

As U.S. government agencies seek to apply AI across their operations, few have adequate access to supercomputers and the deep expertise required to operate the technology and test potential applications on secure infrastructure. 

“The recent executive order on AI encourages federal agencies to reduce barriers for AI adoptions, but agencies often lack the computing environment necessary for experimentation and prototyping,” says Charles Clancy, MITRE, senior vice president and chief technology officer. “Our new Federal AI Sandbox will help level the playing field, making the high-quality compute power needed to train and test custom AI solutions available to any agency.” 

MITRE will apply the Federal AI Sandbox to its work for federal agencies in areas including national security, healthcare, transportation, and climate. Agencies can gain access to the benefits of the Federal AI Sandbox through existing contracts with any of the six federally funded research and development centers MITRE operates.

Sandbox capabilities offer computing power to train cutting edge AI applications for government use including large language models (LLMs) and other generative AI tools. It can also be used to train multimodal perception systems that can understand and process information from multiple types of data at once such as images, audio, text, radar, and environmental or medical sensors, and reinforcement learning decision aids that learn by trial and error to help humans make better decisions.

“MITRE’s purchase of a DGX SuperPOD to assist the federal government in its development of AI initiatives will turbocharge the U.S. federal government’s efforts to leverage the power of AI,” says Anthony Robbins, vice president of public sector, NVIDIA. “AI has enormous potential to improve government services for citizens and solve big challenges, like transportation and cyber security.” 

The NVIDIA DGX SuperPOD powering the sandbox is capable of an exaFLOP of performance to train and deploy custom LLMs and other AI solutions at scale.

About MITRE

MITRE’s mission-driven teams are dedicated to solving problems for a safer world. Through our public-private partnerships and federally funded R&D centers, we work across government and in partnership with industry to tackle challenges to the safety, stability, and well-being of our nation.

Article link: https://www.mitre.org/news-insights/news-release/mitre-establish-new-ai-experimentation-and-prototyping-capability-us

Raimondo announces plans for global network of AI Safety Institutes and future convening in the San Francisco area, where the U.S. AI Safety Institute recently established a presence.

May 21, 2024

Today, as the AI Seoul Summit begins, U.S. Secretary of Commerce Gina Raimondo released a strategic vision for the U.S. Artificial Intelligence Safety Institute (AISI), describing the department’s approach to AI safety under President Biden’s leadership. At President Biden’s direction, the National Institute of Standards and Technology (NIST) within the Department of Commerce launched the AISI, building on NIST’s long-standing work on AI. In addition to releasing a strategic vision, Raimondo also shared the department’s plans to work with a global scientific network for AI safety through meaningful engagement with AI Safety Institutes and other government-backed scientific offices, and to convene the institutes later this year in the San Francisco area, where the AISI recently established a presence.

COMMERCE DEPARTMENT AI SAFETY INSTITUTE STRATEGIC VISION

The strategic vision released today, available here, outlines the steps that the AISI plans to take to advance the science of AI safety and facilitate safe and responsible AI innovation. At the direction of President Biden, NIST established the AISI and has since built an executive leadership team that brings together some of the brightest minds in academia, industry and government.

The strategic vision describes the AISI’s philosophy, mission and strategic goals.  Rooted in two core principles — first, that beneficial AI depends on AI safety; and second, that AI safety depends on science — the AISI aims to address key challenges, including a lack of standardized metrics for frontier AI, underdeveloped testing and validation methods, limited national and global coordination on AI safety issues, and more. 

The AISI will focus on three key goals: 

1. Advance the science of AI safety;
2. Articulate, demonstrate, and disseminate the practices of AI safety; and
3. Support institutions, communities, and coordination around AI safety.  

Read the full Department of Commerce release.

Article link: https://www.linkedin.com/posts/nist_ai-artificialintelligence-responsibleai-activity-7198709049062760448-6SMp?

“If I worry about one workforce, it’s the contracting workforce,” said Doug Bush.

Anastasia Obis

May 16, 2024 7:03 am

While the Defense Department’s acquisition budgets have grown significantly in recent years, there are not enough contracting officersto manage their ever-increasing workload. 

The Army, for example, has about 9,000 acquisition workers, but they have been stretched thin since their workload has doubled in the last couple of years.

Doug Bush, the Army’s acquisition chief, said the service is currently focused on giving its contracting officers better technology and tools to increase efficiency, but more people are needed to provide acquisition support to the Army.

“If I worry about one workforce, it’s the contracting workforce,” Bush said during a Senate Appropriations Subcommittee on Defense hearing on Wednesday.

“They doubled their workload, frankly. They did COVID and then they rolled straight into Ukraine. I think [we need] a little help in both realms. Efficiency investment and perhaps some more people would be warranted.”

Bush said they would not be able to beef up their acquisition workforce in the coming year with the current level of funding.

Undersecretary of Defense for Acquisition and Sustainment William LaPlante said that the department is in the midst of rebuilding some parts of its contracting workforce. 

Several factors contribute to the department’s acquisition worker shortage. The Defense Department’s acquisition workers are highly sought after by private companies and other agencies within the federal government, which creates a gap for the department. In addition, many contracting officers were deployed to active conflict zones in Iraq and Afghanistan, which led to burnout.

“I would say in pockets we still have work to do,” said LaPlante.

Nickolas Guertin, the assistant secretary of the Navy for research, development and acquisition, said he has long advocated for a better implementation of modular and open architectures in military equipment and systems, which increases competition and fosters innovation. It also increases the volume of contracts that need to be managed.

“Contract officers are a key component of our future. We need contract officers to grow,” said Guertin. “Honestly, the Navy grows great contract officers because people keep hiring them. That’s something we continually have to refresh.”

Guertin said while there is a plan in place to increase the number of its contracting officers, the service needs help from Congress.

        Read more: Defense 

The Air Force’s main area of need is the software workforce expertise, said Andrew Hunter, the Air Force’s acquisition chief. But the service has been utilizing its acquisition workforce development pilot for the last two decades to bring in its acquisition workforce.

“I personally believe it shouldn’t be permanent. But at a minimum, we need to extend it because that is a key way of how we keep our talent,” said Hunter.

A study from Rand found that the department’s acquisition workforce grew by 57,677, from 128,187 people in 2006 to 185,864 people in 2021. And almost all of the increase was in the civilian acquisition workforce. 

The age distribution of the workforce shifted, with 29% under age 40 in fiscal 2011 to 35% in 2021, indicating that the department has improved the generational profile of its acquisition workforce. And the majority of contracting officers meet or exceed the certification requirements they need to fill their positions. 

Article link: https://federalnewsnetwork.com/defense-main/2024/05/dods-acquisition-workforce-is-stretched-thin/