By Meg Flippin Benzinga
DETROIT, MICHIGAN - November 20, 2025 (NEWMEDIAWIRE) - Roughly one in ten Americans 60 or older has been the victim of some form of elder abuse in their lifetime, while older adults lose a staggering $28 billion each year to financial fraud. Despite efforts, elder abuse and financial fraud have been around seemingly forever with no end in sight. It's proven hard to solve because it is difficult to detect.
Determining who to blame for fraud and abuse is hard when there are several people involved when someone needs caregiving. LogicMark Inc. (OTC: LGMK), the provider of personal emergency response systems (PERS), health communication devices and technology for the growing care economy, is leveraging its patents in AI and game theory to find a more reliable way to figure that out. LogicMark has been enabling seniors to live independently on the go and at home thanks to its suite of devices, software and AI and machine learning technology – and its patents, including the ones around incentive misalignment and AI game theory – for almost 20 years.
Spotting Ulterior Motives
To protect from elder abuse and fraud, LogicMark holds patents focused on detecting incentive misalignment in caregiving environments, which occurs when the goals of the paid caregiver conflict with their clients’ best interests, leading to potential abuse or fraud. Its patents analyze the activities and motivations of every party or “player” involved in the care of the elderly person using AI and machine learning. The analysis ensures all the players in the care protocol are acting in alignment with the person’s safety and security in mind.
The system will first use AI and machine learning to assess the goals, interests and behaviors of all of the individuals involved in caregiving to determine what their alignment should be. Then game theory AI applications simulate multiple “games” or scenarios using AI and machine learning to determine if there are any misalignments of interests between the “players” and the person receiving care, caregivers, family members, friends or agencies involved in the care. The intent is to always ensure the best possible outcome for the person who needs care. If any misalignments are spotted, they can be flagged and reported to the appropriate individuals.
Real Life Scenarios
Consider a situation where an elderly person’s family hires an agency to provide five hours of daily care starting at 8:00 a.m. LogicMark’s device records that the caregiver did not arrive at 8:00 a.m. and didn’t stay for five hours. This is recognized as a misalignment of interests and is reported to the family for follow-up with the agency.
In another example, someone is being cared for by the family’s 25-year-old granddaughter, who is responsible for buying groceries each week. Prior to this arrangement, the weekly grocery bill averaged $150, as captured by LogicMark’s service, potentially through a partnership for grocery orders with a delivery service. Over the six weeks that the granddaughter was responsible, the weekly bill steadily increased to $280. The incentive misalignment and game theory AI detects this change in pattern which is inconsistent with the past, and alerts the family. This could be due to the granddaughter purchasing personal items for herself – or a conversation could reveal that the grandmother now prefers more expensive groceries. Either way, the system helps surface the issue for the family to resolve. Without LogicMark’s technology, the family wouldn’t know about either instance.
With the patents, LogicMark is helping pioneer the use of AI to help prevent elder mistreatment and financial exploitation in caregiving environments. By tracking and modeling behaviors using AI, LogicMark is able to identify any misalignments in activity that may lead to less-than-optimal care for the elderly person. With elder abuse continuing to grow, and with financial fraud costing the nation tens of billions of dollars a year, tools like this are clearly needed.
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This content was originally published on Benzinga. Read further disclosures here.
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