The Changing Landscape in Public Safety

Syracuse firefighters respond to fire on Fitch Street

By Eloy Vega

Public safety has traditionally been an arena that requires intense human labor, manual investigation, and a hands-on approach. However, as the world rapidly transforms, it has become essential to understand the evolving landscapes in the public safety sector. New operating environments call for continuous adaptation, innovative thinking, and collaboration among emergency services organizations.

For example, artificial intelligence (AI) and deep learning have already greatly influenced a wide range of industries, from healthcare to transportation, allowing us to perform previously unimaginable things.

AI

Can identify patterns in vast data sets.
Recognize faces in photographs.
Understand human speech.

Deep Learning

A branch of AI.
Can analyze data and extract insights by employing numerous layers of neural networks.
This method has allowed us to gain insight into complicated systems, such as the human brain.

As we continue exploring and applying these technologies for various uses, we must be agile and forward thinking to effectively address the challenges and opportunities in this dynamic environment. These technologies have significant potential to revolutionize the public safety sector, introducing a new level of efficiency and effectiveness while engaging with communities and aligning strategies with changing needs.

The Importance of Understanding Changing Landscapes

Human beings are extraordinarily complex, capable of a wide range of emotions, ideas, and sentiments. We have a wealth of life experiences that affect societal dynamics, climate, and technology changes, all of which are constantly changing the public safety scene. Changes in demographic composition, urbanization trends, social unrest, the growing danger of natural catastrophes due to climate change, and the spread of digital technologies all influence the environment in which public safety agencies work. Therefore, keeping up with these developments is advantageous and necessary for a public safety professional.

Recognizing these shifting environments enables better-informed decision making and planning, ensuring businesses can anticipate and adapt to difficulties rather than simply reacting to them. For example, understanding the rising frequency and intensity of climate-related disasters may encourage investment in enhanced prediction and mitigation techniques. However, understanding the increasing incidence of digital hazards may motivate you to install effective cybersecurity solutions.

The Impact of Emerging Technologies

The growth of AI and deep learning is one of the most important recent advancements. These technologies can completely transform the public safety sector by delivering a new level of efficiency and effectiveness.1

AI uses algorithms to simulate human intellect, allowing computers to learn from and make data-driven judgments. Deep learning, a subclass of AI, uses neural networks with several layers (thus called “deep”) to learn from massive quantities of data. As a result, it can discern patterns that a person or a less advanced AI system would find too difficult.

AI and associated technologies are rapidly being applied in the firefighting profession. For example, AI algorithms are being used to enhance real-time fire detection and precisely determine the size and form of a fire.2 AI-enabled drones may also be used to check and monitor dangerous locations. Machine learning algorithms are being used to predict changes in weather or population density trends.3

A Fascinating, Cutting-Edge Technology with the Potential to Alter the World of Firefighting

Deep learning improves the effectiveness and efficiency of firefighters’ jobs.
It analyzes massive databases of firefighting data to identify trends and patterns.
This allows firefighters to estimate when fires will occur before they start, allowing them to respond swiftly and efficiently when an emergency develops.

Furthermore, deep learning is increasingly being used to develop virtual situational awareness simulations that assist firefighters in training for future scenarios with up-to-date data rather than depending solely on traditional education methods.4

How AI and Deep Learning Enhance Public Safety

AI and deep learning can be transformative factors in public safety, improving emergency reaction times, streamlining operations, and relaying important information. They can, for example, do the following:

Use proprietary algorithms to anticipate fires before they occur.
Detect heat from dwellings.
Detect hazardous environmental pollutants.
AI can analyze massive volumes of data to identify where catastrophes are likely to occur, allowing companies to manage risks in advance. (For example, AI may use past data to forecast locations most likely to have wildfires, allowing for the implementation of preventive measures.)
During an emergency, AI can also increase communication with people.
Natural language processing, a type of AI, may assess and reply to public questions, delivering critical information during crises.

With this new technology, firefighters can be more efficient and effective in keeping people safe. AI will become more pervasive in our lives in the following years, as AI-powered devices help us better analyze data and judge our surroundings.

Additionally, algorithms can automate ordinary jobs, allowing employees to focus on more complicated and critical duties. This might include everything from keeping records to assessing incoming data and highlighting high-priority situations. Neural networks can assist in determining the fastest and most effective response to an emergency by assessing many data streams in real time. Deep learning algorithms might optimize emergency vehicle routing by considering factors such as traffic, road conditions, and the nature of the incident.

AI and deep learning can alter public safety organizations, making them more nimble, cost-efficient, and effective. AI and deep learning may help public safety organizations discover patterns faster, prioritize resources more effectively, and adapt to changing conditions by leveraging data-driven insights. Understanding the shifting terrain and embracing emerging technology can help us construct a safer future.5

That said, it is also critical to navigate these developments with caution. Data privacy, ethical AI usage, and possible job displacement due to automation all require careful thought and suitable legislative safeguards.

Will I Be Replaced by AI?

Although the subject of whether AI, deep learning, or comparable technology may eventually replace first responders, such as firefighters and paramedics, is a difficult and contentious one, the short answer is: No. Not likely, or anytime soon, at least.

Here’s why the necessity for human engagement in essential jobs will persist:

First responders offer vital features to emergency situations that AI and computers struggle to imitate, such as critical thinking, situational evaluation, and empathic communication.
The ability to make quick judgments and deliver empathic engagement is critical during high-pressure situations. These human characteristics cannot be easily replaced by technology.
Emergency scenarios include unpredictability, dynamic conditions, and high degrees of uncertainty.
Human first responders are highly adaptable, able to make split-second judgments and respond quickly to rapidly changing conditions.

These distinct qualities are not readily replaced by AI systems, emphasizing the irreplaceable significance of human responders in dealing with the problems provided by unexpected and dynamic situations.

Further, firefighters and paramedics regularly perform physically strenuous activities such as operating heavy equipment, traversing rugged terrain, and providing hands-on medical care. These duties involve physical strength, dexterity, and the ability to solve issues quickly. Current AI systems are ill-equipped to undertake these physical activities, and they lack the physical presence and capabilities that human responders have.

Another critical factor to consider is the importance of personal connection and trust during catastrophes.

Human first responders provide reassurance and comfort to individuals affected by the event.
Human responders have the unrivaled capacity to create trust, establish rapport with persons and stressors, and give emotional support in ways that technology cannot wholly replicate.
To these ends, emerging technologies are more likely to be integrated into first responder workflows to assist and enhance their skills.
AI is increasingly altering the way organizations and individuals live and interact.
AI may assist in the automation of operations, improving accuracy and efficiency and even supplementing human intellect.

Ethical and Moral Issues of Emerging Technologies

Privacy and data security are critical factors when using intelligent machines and machine learning in fire and emergency services companies. These technologies need to collect and analyze large volumes of data frequently, particularly personal and sensitive information. Organizations must put in place robust safeguards to protect the privacy and security of their employees to prevent illegal access or misuse.

As public safety agencies embrace emerging technologies such as AI and deep learning, they must take the required precautions to prevent unwanted access to critical data.6

Leadership in the fire service must ensure that security policies are in place to do the following:

Manage access rights.
Anonymize or pseudonymize personal information.
Conduct regular assessments and audits.
Provide training and awareness on data privacy protocols.
Develop a response plan for potential security breaches.
Remain compliant with applicable regulations.

Employees must also be informed of applicable data privacy regulations to play an important role in protecting sensitive information from unauthorized access.

Our service leaders must foster an awareness culture inside the business by training employees in best practices for handling data security. To ensure the best data security, leaders should regularly evaluate and change access privileges.

Strategy Is Key

Creating a well-defined response strategy is essential for safeguarding sensitive information. In the case of a security breach, immediate and urgent action is required to limit damage and rebuild stakeholder confidence. Changes to corporate policies, procedures, and security measures may be implemented, as well as notification of the occurrence to individuals impacted. The response plan should give specific instructions on incident response protocols, notification requirements, and post-event mitigation actions.

AI algorithms in brain models are prone to prejudice, which can lead to discriminating effects. To promote fair and equal treatment toward individuals, fire and emergency service organizations must be aware of these prejudices and take actions to reduce them, regardless of race, gender, or socioeconomic background. Proactive approaches for addressing biases and guaranteeing fairness in AI systems include varied and representative training data, regular algorithm or bias attention audit, and continuing system performance monitoring. They also entail adding fairness concerns to the design and development of AI systems to integrate transparency mechanisms, explainability, and accountability in decision making.7

Deep learning models can be exceedingly complex and difficult to comprehend. This lack of openness may lead to various problems, including the development of models that make judgments based on erroneous or biased data. To retain responsibility and confidence, first responders in companies must fully grasp how these technologies arrive at specific findings or suggestions in crucial situations.

Further, as these technologies play a more significant part in decision-making processes, creating clear lines of duty and accountability is critical. Fire and emergency services companies must evaluate who is ultimately accountable for the actions and results of AI systems, particularly when errors occur.

As importantly, we must also consider public opinion and faith in the mechanisms adopted by our firms. The implementation of AI and deep learning technology in emergency services might raise concerns and mistrust among the public and other stakeholders. To preserve trust and acceptability, organizations must be honest about their use of these technologies, clearly articulate their benefits, and aggressively address concerns.

Addressing these ethical and moral concerns necessitates considerable thought, transparent policies, and constant monitoring. To negotiate these complex ethical problems, fire and emergency services organizations should adopt ethical rules and frameworks to ensure the responsible and accountable use of AI, deep learning, and other related technologies.

Moving Forward with Advancing Technology

As we go into a more digital environment, public safety agencies must understand the value of adopting cutting-edge technology, such as AI and deep learning, into their operations. Fire departments worldwide have begun to use cutting-edge technologies to simplify operations and improve efficiency. These technologies, ranging from predictive analytics software to wireless communication networks, are transforming the way fire departments respond to catastrophes. This will keep our communities secure while also looking into the future of public safety.

Remember the following points for the future:

Fire departments must keep abreast of technological advances to continue serving their communities successfully.
The adoption of new technology will transform how fire departments function in the future, allowing them to safeguard lives and property more effectively than ever before.
Thanks to AI-powered technologies, firefighters will be able to keep up with changing environments and respond quickly and accurately in dangerous scenarios.
Public safety agencies may obtain useful insights into possible threats and adopt a more proactive approach to keeping their residents safe by harnessing these powerful new technologies.

As new technology becomes available, the fire and emergency services sectors are quickly evolving. Fire service officials owe it to their communities to offer the best service possible. One way to do so is to embrace new technology that might help them respond to crises quicker and more efficiently.

Thanks to AI, deep learning, and machine learning algorithms, first responders now have access to strong tools that may help them identify fires sooner, respond to situations faster, and obtain vital situational awareness insights. It’s clear that the future of public safety is becoming more digital and, if intelligently managed, is a future that has enormous promise.

ENDNOTES

1. Abid, S. K., Sulaiman, N., Chan, S. W., Nazir, U., Abid, M., Han, H., Ariza-Montes, A., & Vega-Muñoz, A. “Toward an Integrated Disaster Management Approach: How Artificial Intelligence Can Boost Disaster Management,” Sustainability. 2021. bit.ly/4bVACUn.

2. Raveendran, N. “Future of Smart Firefighting with Artificial Intelligence.” Bournemouth University, December 2020. bit.ly/4bX6Hvi.

3. Prasanna, Yang, L., & King, M. (n.d.). “Guidance for developing human–computer interfaces for supporting fire emergency response.” Risk Management, July 2013. bit.ly/3wSe9sy.

4. Mallouhy, R. E., Guyeux, C., Jaoude, C. A., & Makhoul, A. “Machine Learning for Predicting Firefighters’ Interventions Per Type of Mission,” 2022 8th International Conference on Control, Decision and Information Technologies (CoDIT). May 17-20, 2022.
bit.ly/4bFAc4T.

5. Alidoost, F., & Arefi, H. “Application of deep learning for emergency response and disaster management,” Proceedings of the AGSE Eighth Interntional Summer School and Conference, 2017.

6. Cohen, W. M., & Levinthal, D. A. (n.d.). “Absorptive Capacity: A New Perspective on Learning and Innovation,” Administrative Science Quarterly, March 1990.
bit.ly/3yBpUUJ.

7. Ross, W., Morris, A., Cunha, A., & Ulieru, M. “Discovering best practices in emergency response with combined physical and organizational simulation,” 24th Canadian Conference on Electrical and Computer Engineering (CCECE), Niagara Falls, ON, Canada, 2011. bit.ly/3V7Umh4.

ELOY VEGA is the fire chief, EMC, and fire marshal for the City of Port Neches (TX). Prior to this, he retired after 23 years as a district chief with the Laredo (TX) Fire Department. He completed the master of public administration program at Sam Houston State University and is currently pursuing a PhD in fire and emergency management administration at Oklahoma State University.