DCPP-01 information hunger - DSCI certified Privacy Professional

Save the Children’s research suggests that income shortages in poorer households, when combined with shocks such as natural disasters or conflict, reinforce poor health and nutrition and thereby lead to higher rates of child deaths.

Hunger also keeps children out of school and limits their ability to concentrate once in school. Studies conducted by Save the Children indicate that learning achievement among children from poor families is systemically lower than their peers.

An increasing number of young people live in a state of poverty, unemployment and/or underemployment. Over one-fourth of young people in the world cannot find a job paying more than $1.25 per day, the international threshold of extreme poverty. Three quarters of young workers ages 15-29 are employed in the informal sector, increasing the possibility of exploitative or hazardous working conditions.

Save the Children’s Household Economy Approach (HEA) outcome analyses have found that the cycle of vulnerability due to chronic hunger and a lack of livelihoods security may lead poorer households and children to pursue unsustainable and dangerous livelihoods opportunities, to withdraw children from school, or to encourage early child marriage or harmful child labor.

Food security, livelihoods protection and strengthening, and poverty alleviation programs are an essential underpinning to ensuring the survival, education and protection of children, such that the intergenerational cycle of poverty can be broken.

To address this, Save the Children:

• Provides food assistance to families following a natural disaster or emergency.
• Builds household and community resilience to food security and economic shocks and stresses.
• Strengthens socio-economic conditions to Boost standards of living and the ability of families to provide for their children.
• Provides youth with the skills and linkages they need to earn and manage a decent income.

The growing importance of data science, and the increasing role of information professionals in the management and use of data, are brought together in Practical Data Science for Information Professionals to provide a practical introduction specifically designed for information professionals.

Data science has a wide range of applications within the information profession, from working alongside researchers in the discovery of new knowledge, to the application of business analytics for the smoother running of a library or library services. Practical Data Science for Information Professionals provides an accessible introduction to data science, using detailed examples and analysis on real data sets to explore the basics of the subject.

Content covered includes:

• the growing importance of data science
• the role of the information professional in data science
• some of the most important tools and methods that information professionals may use
• an analysis of the future of data science and the role of the information professional.

This book will be of interest to all types of libraries around the world, from large academic libraries to small research libraries. By focusing on the application of open source software, the book aims to reduce barriers for readers to use the lessons learned within.

Baylor School of Education offers several programs typically leading to professional licensure or certification. Click the links to see professional licensure disclosure information for each one. These links provide information about program compliance with licensure standards in all U.S. states and are particularly important references for students who believe they may not choose to practice or teach in the state of Texas. 

Educator Certification
Applies to SOE programs that prepare for licensing for teachers (BSEd, MAT), principals (MA School Leadership), and superintendents (EdD in K-12 Educational Leadership)

Educational Psychology
Applies to licensure programs in Applied Behavior Analysis

Educational Specialist
Applies to programs leading to licensure as a School Psychologist

General Information:

Background- Baylor University offers several programs leading to professional licensure within the State of Texas.  States vary in what professions they require to be licensed and how licensure functions.  Some states require an individual to graduate from an approved program.  Others require an individual to “meet [the] certification requirements of a national organization”.  A specific amount of training can also be required as well as passage of an exam based on a state requisite exam score.  Often, licensed professionals must complete continuing education on an annual basis (National Center for Complementary and Integrative Health, 2018).

State Authorization- Baylor is a member of the National Council for State Authorization Reciprocity Agreement (NC-SARA) which allows us to provide distance learning programs (both online and in the form of supervised field experiences) and coursework to residents of states other than Texas.  NC-SARA membership, however, does not grant reciprocity or exempt us from state professional licensing requirements.  As a result, licensing requirements in Texas may not be recognized as sufficient to obtain a license in any other state.

Relocation- Relocating while in the course of a program to another state may have impacts if the student can remain in the program, meet the state licensure requirements and/or continue to receive financial aid funding. Prior to considering relocation, please complete the Location Form and contact your program advisor to discuss authorization and licensure eligibility requirements. 

International Students- Prior to enrolling in any program at Baylor University, prospective students living and/or working outside of the United States should confirm with the appropriate certifying agency whether successful completion of any degree program at Baylor will meet the credentialing requirements of the country in which they intend to seek employment, as to certain types of employment or for advanced/specialized educational programs.

Students Responsibility- Students should review the specific academic requirements for the program in which they are enrolling, including those related to practicum/internship as well as pre-qualifications for licensure such as the need for a criminal background check. We highly recommend that students contact the applicable licensure board(s) in their state of residence or in the state where they intend to obtain a license before beginning an academic program that results in licensure and prior to beginning any internship/practicum. Many licensure boards have additional requirements beyond successful degree completion to obtain a license. Please be advised that state laws, regulations, and policies may change at any time. Changes in requirements can impact the program's ability to meet educational requirements for licensure. It is the responsibility of the student completing the licensure program to check with the licensing board(s) in their state of residence or in the state in which they intend to obtain a license for the most accurate information and requirements. Baylor shall not be held liable if the student is unable to qualify for licensure or certification in any jurisdiction or cannot obtain a practicum/internship location.

Information about all of BU’s programs leading to licensure can be found here:

Professional Licensure Disclosure by Program

Essential Law for Information Professionals, fourth edition, provides up-to-date and easy-to-follow practical guidance on the law as it affects information management and the principles underlying practice. Using individual cases to illustrate these core principles and contextualise regulations, it cuts through the legalese to provide exactly what's needed in an easily digestible format showing examples of how the law has worked in practice in specific legal cases. The book gives readers the tools to quickly assess legal hazards and identify solutions.

Information law is a particularly fast moving area of law. In the eight years that have passed since the best-selling third edition was published, there have been many changes to the legislation and numerous legal cases which have further developed our understanding of the law. The fourth edition fully reflects those changes, which include:

• a new chapter on library law which covers the legal framework for libraries (concentrating on legislation and soft law relevant to libraries)
• implementation of the GDPR through the Data Protection Act 2018
• a major overhaul of the copyright exceptions, and the 2018 implementation of the Marrakesh Treaty
• the Re-Use of Public Sector Information Regulations 2015 and the implications of the 2018 proposals for a new re-use directive
• extension of the public lending right scheme to e-books
• CILIP's ethical framework.

Readership: Essential Law for Information Professionals is an essential guide for anyone working in the information professions. It is also the ideal legal textbook for students of information studies and librarianship.

Of the 5.9 million children who die each year, poor nutrition plays a role in at least half these deaths. That’s wrong. Hunger isn’t about too many people and too little food. It’s about power, and its roots lie in inequalities in access to resources and opportunities.

It’s widely known that to succeed with AI, a company needs to have some distinctive information. Wolters Kluwer, the Netherlands-based professional information, software solutions and services company that does business in over 180 countries today, has never lacked for that resource. It was founded in 1836 as a schoolbook publishing company, and over the years merged with other publishers and eventually began developing and acquiring digital information capabilities.

Nancy McKinstry, the CEO and Chair of Wolters Kluwer, became its leader in 2003. She began to transform Wolters Kluwer into an expert solutions company, hiring and developing experts with deep expertise in areas like healthcare, tax, risk and compliance, and legal. The company also created a global Digital eXperience Group (DXG) to help speed time-to-market and innovation in digital products, as well as a Global Business Services (GBS) group to provide strategic execution services. Today, the company’s revenues from publishing are less than 5% of the total—down from over 80% when McKinstry became CEO.

By the time AI became more prevalent in the late 2010s, Wolters Kluwer was well into the business of providing “expert solutions” to its customers. At this point there were hundreds of experts in various fields providing expertise to customers, and fortunately Wolters Kluwer captured the data on the advice it provided and the outcomes for the customer. One might notice that this is a perfect situation to begin modeling and predicting those outcomes with machine learning. By 2016, the company had created its first AI-enabled product: CCH IQ used machine learning to help tax service providers identify which clients are affected by changes in tax legislation, assess the impact of the changes on client tax returns, and understand opportunities for additional tax services to clients.

Building AI-Based Product Capabilities

In addition to the data, Wolters Kluwer began to build the necessary capabilities to create AI-based products. Its Financial and Corporate Compliance (FCC) division created an organization—called Customer Information Management/Operational Excellence (CIOx) —to better understand customer needs and build new products and solutions. Members of the group are expected to spend time with customers and identify their needs. The goal is to create solutions that fit customers’ workflows and develop solutions that address their problems.

The group developed a product development process with the steps of “ideate, test, incubate, scale.” A team of product developers employs the process. The company also began to hire a number of data scientists and embedded them with domain experts. Its formula for product development success became “Data + Domain Knowledge + AI = Solution.”

The CIOx team, working closely with the business lines within the FCC division, also developed a set of principles for successful product development projects. For example, the team recognized that it needed an equal seat at the table with other team members, and should be viewed as data-driven, trusted advisors. They wanted to be seen not as a research group, but as having a solution mindset. The metrics for their success—and resulting reward mechanisms—should be the same as the businesses with which they were working. In short, they viewed themselves as “blue-collar AI workers” focused on achieving outcomes rather than simply developing great models.

In addition to high-quality people and operating principles, CIOx has also established a set of technology capabilities to accelerate AI-based product development. They have created a series of platforms that shield developers from legacy technology and enable faster data access and modeling. A set of data stores and feature engineering repositories are part of this capability. Wolters Kluwer has also adopted a machine learning operations (MLOps) workbench for sophisticated neural network model development, deployment, and ongoing monitoring.

Analyzing Legal Bills with AI

One of Wolters Kluwer’s most prominent AI products is called LegalVIEW® BillAnalyzer, offered by Wolters Kluwer ELM Solutions, part of the Legal & Regulatory division. It supports large companies’ chief legal officers in reviewing law firm invoices for compliance with outside counsel billing guidelines. It compares these companies’ legal services agreements with what law firms actually bill them for, and frequently finds errors in the bills. Beginning in 2017, LegalVIEW BillAnalyzer was based on human review by legal experts. It was a successful but labor-intensive product.

Now, however, AI systems extract key provisions from legal services agreements—and automatically analyze bills. LegalVIEW BillAnalyzer has over $160 billion in legal invoices to use in training machine learning models. For each line item on the bill, a model calculates a risk score—i.e., the likelihood of a billing anomaly based on provisions in the legal services agreement and adjustments in past data. If, for example, the outside law firm is billing 16 hours for a deposition that usually requires only four hours for that particular type of case, it will assign that line item a higher risk score. If the customer verifies that the line item needs adjustment, that data is used to refine the model and can increase the risk score.

LegalVIEW BillAnalyzer can save companies up to 10% on their outside legal service costs and increases compliance with billing guidelines by up to 20%. The system also saves in-house counsel considerable time on investigating instances of overbilling.

Generative AI Products in the Making

Wolters Kluwer, like many companies, is also experimenting with generative AI. But consistent with the CIOx focus, it has specific products in mind. One of the forthcoming generative AI-enabled products, for example, involves an existing product called OneSumX® ProViso. It employs AI technology, validated by regulatory experts, to monitor, capture, review, and summarize vast amounts of changing laws and regulations for banks, insurers, and other financial services companies. This has been a successful, expert-based product for several years. Now, however, the CIOx group is working to determine how GPT-4 can add value to the offering. It is having the language model read a regulation and summarize it with thus-far promising results. The technology appears to do an excellent job of creating a first draft and produces outputs similar to human financial services legal experts. Ultimately, the business is working with product owners to identify potential use cases and understand how ChatGPT and other generative AI solutions might help its customers.

Wolters Kluwer also has maintained legacy computer systems throughout the company that have been installed for many years and are specific to a particular content domain. The company has explored the idea of training its employees in old and new programming languages in order to translate the old code into new code, but this is very time-consuming, and it is difficult to attract and retain talent for the job. But since Wolters Kluwer is often working in compliance-oriented domains, it has always been important to preserve the quality of program code.

Now the company is exploring the idea of using GPT-4 to translate obsolete program code into new languages, as well as to produce documentation of the new code in English. Notably, product operations certified in several business areas are working with data scientists to analyze and perhaps rejuvenate over one million lines of code. Wolters Kluwer is adding artificial intelligence capabilities into its products, allowing it to supplement deep domain expertise with the latest technology.

The Ongoing Role of Humans

Wolters Kluwer has no intention, however, of using AI to replace its human employees. The company has invested heavily in employee education and “upskilling” programs, with the assumption that jobs of the future will rely heavily on AI and other new technologies, working side by side with its experts. Grassroots communities within the company, including one called “Addicted to Learning” with 800 members, have arisen to encourage further learning about new technologies, including AI and generative AI. The assumption is that such focused education will drive innovation and future demand for Wolters Kluwer products. Thus far, at least at Wolters Kluwer, this maxim has proven to be an accurate indicator of innovation for 187 years.