The Importance of AI in Public Safety
No longer the stuff of science fiction, the Harvard Business Review reports that the use of artificial intelligence (AI) is skyrocketing. In fact, in a recent survey 86% of respondents called AI “mainstream technology.” Of course, people may still be leery due to Hollywood’s parade of movies with robots taking over the world. However, the AI of today is designed to assist humans with everyday tasks. And when it comes to public safety, it can make responders’ lives easier and safer while also improving patient outcomes.
What is Artificial Intelligence In Public Safety?
Computer scientist John McCarthy first used the term artificial intelligence in 1956. He defined AI as “the science and engineering of making intelligent machines.” Today, AI is known for its ability to mimic human thought to perform routine tasks. Every time you plug a destination into your car assist, unlock your phone using facial recognition or ask Siri to add to your grocery list, you’re using a form of AI.
AI is playing an important role in public safety. PSAPs can now receive notifications well before a voice call for help comes in. Strategically placed listening devices and an AI algorithm can continually listen for and recognize the sound of a gunshot and triangulate where it came from. Audio and video surveillance can recognize a motor-vehicle accident and ask for the right type of assistance before a call for help is made, cutting down on the time for help to arrive.
5 Ways AI Can Benefit EMS and Fire-Rescue
AI is also helping to support EMS and fire-rescue. This technology has been shown to greatly benefit PSAPs when every second counts, decreasing ambulance response times and patient mortality. Here are some of the ways artificial intelligence is helping responders and improving public safety:
1. Assisting and Predicting
Being agile and efficient is critical in this industry. The smallest of delays or the slightest bit of misinformation can have significant implications for the communities telecommunicators and EMS teams serve. With assistive AI, software can provide greater insight during critical situations, giving 911 personnel better situational awareness during the incident and improving outcomes for emergency response.
For example, AI gathers data over time and offers predictions that help 911 responders optimize coverage and response time. It can inform personnel as to when and where calls are likely to happen, recommend the placement of resources to reduce how long they may take to arrive, give the most efficient route to get there by avoiding traffic, and provide the best resource to respond to the call based on call type and system workload.
2. Managing Data
At any PSAP, managing the flow of data is critical. Using AI, call centers are able to build systems and models that will help telecommunicators see a more accurate picture of any given situation to better inform the right responders. Based on the information provided, it may even recommend a different type of response, predict who will clear from a call next, and start the movement of resources to provide the best response for the next call.
AI is helping dispatch to plan on-scene service, offering considerations based on the patient’s condition, age and weight; the necessity of IV fluids, antibiotics or oxygen; whether the patient needs a stretcher or wheelchair; and much more. This all helps them send the right response team to the scene and get the patient the care they need quickly and efficiently, reducing over-triaging of patients and decreasing the cost to operate a fleet of resources.
3. Handling Call Volume
The National Emergency Number Association (NENA) reports that there are approximately 240 million calls made to 911 each year. This volume of calls, especially during times of staff shortages, can be a lot for call centers and their telecommunicators to respond to. AI–in the form of chatbots–can help gather caller information, assign priority and notify dispatchers.
The Austin Police Department is a great example of how this can work. Their team is exploring how AI can help support handling call volume during staffing shortages. Electronic Data Management System (EDMS) reports that when a voice request call comes in, an AI component kicks into action with a “virtual officer” that records basic caller information. The AI also provides automatic transcription and translation of non-English languages, which is especially important in diverse regions. It’s easy to see how this AI technology could be applied more broadly to dispatch.
4. Decision-Making Support
Decision-making support is a recent development benefiting responders in a variety of ways. Corti is one new tool in the market; their AI-powered technology listens to emergency calls and prompts the telecommunicator with suggestions, acting like a real-time second opinion helping them to triage calls.
The customizable tool can even be configured to identify a set of keywords associated with a topic and then set up a corresponding alert. A common application for this is the ability to remind telecommunicators to consider specific responses for keywords relating to homelessness, risk of suicide or drug use. Agencies can also hyper-localize the alerts to suit their region and include locations or street names.
5. Gathering Information
AI is always learning, and with each EMS-related interaction, it becomes smarter. Every time a responder inputs information, the AI grows its knowledge to better assist responders and improve patient outcomes. “Through the documentation of patient encounters, today’s EMS providers are essentially the coders of tomorrow’s AI technology,” writes Joe Graw in EMS Technology. “The next time you arrive on scene, remember you’re helping to write the curriculum that will be used to train these AI models of the future.”
Another benefit of AI in healthcare applications is reducing cognitive load on the provider. Research shows that too high of a cognitive workload increases stress, increases failure rates and has a negative effect on work satisfaction. The National Library of Medicine reports that one of the six main causes leading to burnout includes the use of Electronic Health Records (EHRs). However, AI is now doing some of the heavy lifting when it comes to EHR documentation and related tasks, making the EHR more accurate and increasing the quality of care given and overall patient safety and satisfaction.
Why Do We Fear Artificial Intelligence?
Research indicates that approximately one-third of people say they’re afraid of AI, while about one-quarter believe it will be harmful to society. Much of this comes from people’s fear that AI will replace them. While it’s important to always consider the ways AI is used, its main benefit is to support people. Many in public safety have begun to come around. In fact, Police1 reveals that in a recent survey, the majority of public safety leaders now feel very receptive to using AI in their job and 88% of citizens want to see public safety transformed through AI-related technology.
Plus, despite the adoption of AI, jobs aren’t going away. According to the McKinsey Global Institute, 30% of jobs created in the U.S. over the past 25 years have been linked to AI, and companies that employ AI and robotics technologies are creating millions of new openings across the country.
How Logis AI Helps Support 911 Centers
At Logis Solutions, we use artificial intelligence to support the work you do every day. Our goal is to reduce manual and repetitive tasks using AI in order to improve human decision-making and allow responders to focus on higher-priority tasks. This, ultimately, leads to better patient outcomes.
Our customers understand that our technologies are not meant to replace personnel, but to support them, helping them to do more with less. With budgets becoming tighter and resources dwindling, AI just makes sense.
Our cutting-edge CAD technology has been a game-changer for many PSAPs. Available on-premise, in the cloud or via a hybrid solution, Logis software automates important aspects of decision-making for computer-aided dispatch, billing and resource management.
But don’t just take our word for it. “Logis IDS delivers more than what you’d expect in a CAD,” says Kenneth Simpson, COO, MedStar Mobile Healthcare, in Ft. Worth, Texas. “With reliable analytics and detailed reporting, we’re able to confidently provide deployment recommendations to dispatchers based on meaningful data. The ability to support that decision-making really makes a difference in how we serve our community.”
If you’re interested in advancing your organization through AI, Logis Solutions is here to help. Our AI gathers data over time, providing predictive data that will help your team optimize coverage and reduce response times. Our technology will let you know when and where calls are likely to happen, how long they may take, and provide valuable suggestions based on drive times and workload distribution. All this sets you up for continued success, making your operation more efficient and effective and helping you become a leader in EMS.
Want to learn more about Logis Solutions CAD? Contact us today.