Seeking safety in the middle of a rainy night, a victim of domestic violence readily finds counseling and secure shelter for her and her two children. Responding to a public disturbance call, a police officer quickly identifies mental health and housing services for a homeless woman known to be suffering from schizophrenia. A daughter is alerted to a potential problem at her elderly father’s home, as he has not yet recorded taking his necessary medications for the day. In each of these cases, cognitive technology can be a critical tool in helping to protect the vulnerable and empowering the vulnerable to help themselves.

Cognitive technology is designed to combine human intelligence with a range of artificial intelligence capabilities such as machine learning, natural language processing, image analysis and reasoning systems—creating an augmented intelligence that amplifies the impact of what humans and machines can do separately. When applied to social services, this technology can enable individuals in need to better manage their own well-being. It can also help strengthen and extend our social safety nets’ reach to at-risk groups by addressing some of the key challenges that typically impede provision and delivery, such as data inaccessibility, complexity and the rate of caseworker churn.

Reaching those in need

Social services agencies and organizations gather immense amounts of data, yet insight and decision making derived from this data can be hindered by inaccessibility. “One of our greatest challenges is accessing and using unstructured data in any meaningful way,” notes Daniel Stein, co-founder of Stewards of Change, an organization focused on improving human services.

Cognitive capabilities can unlock accessibility barriers by enabling the analysis of structured and unstructured data—including that contained within reports, hand-written notes, materials not yet digitized, social media, audio, video, photographs and silos within and across agencies. This additional insight creates a more complete picture of an individual’s needs and conditions. Not only does this improved data management mean that caseworkers can focus more on human interactions instead of mountains of unwieldy data, it can also result in personalized, customer-centric service plans.

Caseworkers spend as little as 20 percent of their day on human interaction. Paperwork and other non-interactive tasks consume up to 50 percent of caseworkers’ time.

– Source: Unlock the Power of Data for More Effective Social Programs

The growing complexity of the social services landscape provides another challenge to provision and delivery to individuals in need. There are many programs that exist across multiple agencies at various levels of government, each with different sources of funding and mandates; and, the regulations, procedures and resources around these programs continually change. As noted by Edward Blatt, Director of Cúram Research Institute, “a caseworker who’s trying to figure out how to help the person sitting in front of him / her could have dozens or hundreds of options out there… the question is how do you weed through that and find the best mix to meet the needs of this person?” Cognitive technology—through data mining, trade-off analytics and personality insights—can enable understanding of this dynamic environment, helping both caseworker and individual to better match needs to available services in real time.

Problems associated with caseworker churn and retention also plague social services, taxing valuable resources and impeding support for those in need. In the United States, social worker turnover is as high as 90 percent per year, with heavy workloads, including paperwork, as a major contributing factor. In the United Kingdom, 42 percent of social workers surveyed said they left work at the end of the day with serious concerns about at least one of their cases—concerns linked to their inability to complete paperwork.

Cognitive technology can help alleviate workload related to caseworkers’ management of data and knowledge. This can lead to less churn and burden placed on experienced caseworkers filling in the gaps, while also potentially leading to fewer mistakes and missed opportunities—enabling higher quality service for at-risk groups.

Cognitive technology can help keep people up to date on policy and practice, and help assess what best practice is.

– Stuart Venzke, Associate Partner, Human Services for U.S. State & Local, IBM

Further, since cognitive-enabled tools help measure and track outcomes, and can learn and be trained based on the data ingested, caseworkers can continually improve service plans over time. As described by IBM Social Services Expert Deepak Mohapatra, “old analytical process-based systems aren’t going to get you anywhere. Cognitive technology can digest 30 years of raw data to train the system on how to understand an assessment, what the case notes say and what outcomes were realized, enabling social workers to build service plans with insight based on decades of knowledge.”

As the use of cognitive technology within social services grows over time, large-scale insight can provide a macroscopic view of groups at risk and which service plans and actions are most effective—globally, regionally, by cohort, as well as by individual needs and conditions. Early warning indicators could become apparent, enabling prevention or mitigation for matters related to both public and individual well-being. Finally, the collaborative nature of these tools around data and knowledge-sharing also means stakeholders across the care ecosystem can become better connected and informed, helping them better protect individuals who are unable to help themselves.

Protecting those at risk

Each year, approximately 40 million children are abused worldwide; while one in four adults report being abused as children. Even when the abuse stops, its repercussions continue. Victims of childhood abuse are more prone to challenges such as teen pregnancy, drug use, low academic achievement and mental health issues. In fact, the global economic costs associated with abuse and its devastating aftermath are estimated to be approximately $7 trillion per year.

Social services tools enabled by cognitive technology present great opportunities for significantly improving the lives of vulnerable children. Social workers, for example, can use these tools to better capture and understand the expanse of data that has been gathered and created around children at risk—mining, for example, hand-written notes, criminal reports of known associates to foster care providers, social media, and data that may exist with other health and human service providers. This can enable caseworkers to form a holistic picture of each child and their environment, needs and conditions. These tools, which ingest and understand huge amounts of data in real time, can also readily identify what interventions and service plans have worked best in the past for similar children and situations.

For example, Aspiranet, which currently serves 22,000 youth and families across California, is using natural language inquiry of unstructured data to help youth transition from foster home care to living on their own. By mining and understanding unstructured data, Aspiranet caseworkers can help transitional age youth find safe housing in areas that also offer potential jobs and ready access to public transportation, education opportunities and grocery stores. This analysis helps identify and minimize risk for these youth, while also enabling person-centered collaboration across Aspiranet’s twelve distinct care programs, such as housing, education, life skills and family and community connection. And, through a linked portal, youth are empowered to begin managing their own well-being, such as connecting to employment and medical services. According to Aspiranet CEO Vernon Brown, “we still need humans,” but cognitive technology helps free up caseworkers’ time, enabling them to focus on what matters most, human connection.

With social programs, we’re looking to not only make it administratively less burdensome, but also to see how can we advance and improve human engagement and interaction.

– Karen Rewalt, Offering Manager, Family Assistance Programs, IBM

Cognitive technology can also help the elderly safely age in place. In almost every country, the proportion of people over 60 years old is growing faster than any other age group. According to the United Nations, the number of people aged 60 years or older is projected to grow by 56 percent worldwide by 2030. Given this rising demographic, many governments and human services organizations are exploring how they can help improve the health and well-being of aging groups.

The Japan Post Group (JPG) is tapping into its nationwide infrastructure—including its 24,000 post offices and 380,000 employees—to support the distribution of tablets and apps to help keep Japan’s elderly healthy, connected and safe. Through a simple-to-use app, seniors are provided with reminders and alerts about medications, exercise and diet; information on community activities; and direct online links to services such as grocery shopping. The app also enables seniors to easily communicate with family and medical professionals. Text analytics and accessibility technology, including Japanese natural language analysis and tracking, are used to guide seniors and make the experience more natural. Interactivity, in the form of verbal prompts and repetition of selected options, is used to build confidence that the app understands the seniors’ needs and is working. Through this interaction, the app sheds light on the needs, interests and life patterns of the user, and can provide insight on potential future health risks while empowering seniors to live independently longer.

One important hospital in Italy, the Casa Sollievo Della Sofferenza, uses cognitive technology to improve treatment for patients with dementia, Alzheimer’s and other degenerative disorders. Apps have been developed to help simplify dialog around the disease and its care, engage patients and keep them mentally active, and provide support to caregivers for dealing with daily challenges. The data will also be analyzed at the macro level to help better understand the evolution of the illness, which variables may affect the disease and what treatments work best.

Our goal is to help families adjust to the daily challenges of the disease, and to help the medical staff better understand the disease’s evolution and how it is affected by other external factors. At the same time, we want to help patients preserve and reinforce their memories.

– Angelo Failla, Direttore Fondazione, IBM Italia

In pilots in Italy and the United States, cognitive technology is being combined with the Internet of Things (IoT) to create smart homes and facilities that can support aging in place. “The heart of these projects is to improve the quality of life of the elderly. And with the aging demographic boom, it’s the right time and the right problem to solve,” states Susann Keohane, Global Research Leader for IBM’s Strategic Initiative on Aging.

This combination of IoT and cognitive technologies shows great promise for transforming accessibility, providing new opportunities for the roughly 650 million people worldwide with disabilities. Chieko Asakawa, a computer scientist with IBM Research who has been blind since the age of 14, is exploring how these technologies can be combined to create a technological platform that can help the visually impaired navigate their environment through spoken commands or vibrations, operating like a car’s GPS system. Chieko is hoping to add facial recognition components so that not only objects but also people are identified.

Cognitive technology is also making inroads on improving the treatment of mental disorders, which affect more than 475 million people worldwide. For example, apps that combine gaming and personalization are being developed so that children and emergency responders can, on their own terms and at their own pace, prepare for and recover from the trauma associated with disaster events. Other experts are using the analytical and predictive powers of cognitive technology to conduct psychological autopsies on individuals who have committed suicide to see if early warning indicators can be identified to help with prevention efforts for others.

For those suffering from substance abuse disorders, cognitive technology can help professionals develop more accurate assessments, allowing more individualized plans and personalized support to increase the odds of recovery program completion. Experts are also exploring how the technology can be used to address problems associated with homelessness by better matching individuals to programs across a range of services—for the homeless often are battling health, mental health and / or substance abuse problems at the same time, adding to the complexity of interventions.

Homelessness calls for an ecosystem of social programs. It’s not just about finding shelter, but also often involves health and mental health components as well.

– Karen Rewalt, Offering Manager, Family Assistance Programs, IBM

Unemployment is another factor that can affect, and contribute to, an individual’s vulnerability. “Providing the right services to address this issue is key,” notes Andreas Gollner, IBM Global Public Employment Service Leader. Trade-off analytics, personality insights and predictive capabilities combined can help individuals more readily find work related to their interests and skills, including out-of-the-box opportunities they would not have considered on their own. The Belgian Employment Agency VDAB has used cognitive technology to determine factors that can increase chances for youth to find employment, and how those factors differ among various young job seekers. The agency is also using it to create a model that predicts youth unemployment and to support VDAB career counselors in helping youth find jobs.

Moving forward

While cognitive technology provides great promise for enhancing and extending social safety nets, there are some ethical and trust considerations. There is a possibility for false positives and false negatives with predictive analytics, a critical factor to consider when lives are at stake. There are also legal and financial liabilities associated with its use on developing interventions, as well as issues around data privacy and security. Finally, there is the potential of bias. If biased data is ingested, biased insight and predictions will result.

Despite these potential hurdles, cognitive technology offers great potential for improving care for the most vulnerable. “Cognitive technology will be like having your best caseworker on every case,” says Katie Keating, IBM Watson Care Manager. And, easier-to-access, more personalized services can help individuals at risk better manage their own well-being, getting the right support when they need it.