Current Use of Artificial Intelligence (AI) in Murder Investigations - Draft

Artificial intelligence (AI) is increasingly being used in criminal investigations — including murder cases. The following is a brief overview covering the current use of AI in murder investigations generated with the assistance of ChatGPT.

Facial Recognition & Identification

• Law enforcement uses AI-powered facial recognition to match faces in surveillance photos or video to known databases.  

• Companies like Clearview AI supply massive image databases that police can use to identify suspects.  

• A Washington Post investigation found that some police departments have made arrests based solely on AI facial-recognition matches, without solid corroborating evidence.  

• “Automation bias” is a problem: officers may over-trust AI matches, even when quality of the source image is poor.  

Forensic Analysis

• AI is helping crime labs process evidence faster, for example in complex DNA mixture analysis.  

• According to the DOJ & law-enforcement-focused reports, AI tools are used to prioritize digital evidence, sift through massive data loads (e.g., seized phones, emails), and detect relevant patterns.  

• In digital forensics, AI can help structure and analyze huge volumes of data more efficiently than humans alone.  

Video and Crime Scene Reconstruction

• Video AI is used to enhance grainy surveillance footage, reconstruct crime scenes, and simulating events, helping to identify suspects or clarifying what happened. 

• Object and activity detection in video feeds (like recognizing suspicious behavior) is being explored.   

Predictive Policing and Network Analysis

• AI models can analyze historical crime data to identify potential hotspots or likely criminal networks.  

• There are academic frameworks (e.g., CrimeGAT) using graph neural networks to model criminal networks, giving law enforcement insights into relationships and potential future crimes.  

Legal / Investigation Assistance Tools

• There are early systems like the Language Model-Augmented Police Investigation System (LAPIS) that use large language models to assist officers with legal reasoning during investigations.  

DNA Phenotyping

• Some firms like Parabon NanoLabs use AI to generate 3D facial images from crime-scene DNA. These “Snapshot Phenotype Reports” attempt to predict characteristics like skin color, hair, and facial structure from genetic markers.  

• In some cases, law enforcement has tried to run those AI-predicted faces through facial recognition systems to generate suspect leads.  

• However, this technique is controversial: reliability is questioned, and civil liberties advocates warn about misidentification risk.  

Case Reporting and Documentation

• Some police departments are experimenting with AI chatbots to help write incident reports. For instance, officers in Oklahoma City used AI to draft crime reports from bodycam audio, radio chatter, and other sources.  

Planned / Emerging Uses of AI (or Where AI Is Expanding)

Integrated Surveillance & Real-Time Alerts

• According to the National Institute of Justice, future AI applications could involve video analytics + facial recognition + activity/object detection to detect crimes in real time and alert law enforcement.  

• This could potentially allow more proactive responses (e.g., detecting a violent crime unfolding).

Enhanced Crime Lab Forensics

• Ongoing research is looking at applying AI to trace evidence, crime scene reconstruction, medical / injury evaluation, and latent print (fingerprint) analysis.  

• Automating or accelerating analysis could reduce backlog and help labs process more cases.

Ethics-Aware Investigative AI Frameworks

• Researchers have proposed frameworks like MULTI-CASE, which is a transformer-based, ethics-aware, multimodal intelligence system for investigations. It’s designed to combine heterogeneous data (text, images, networks) and give human investigators transparency and explainability.  

Predictive Tools for Criminal Networks

• Advancing on CrimeGAT, future systems could better predict how criminal networks evolve, who the key players are, and where law enforcement should focus.  

• These tools may help not just in identifying suspects, but in anticipating organized crime structures.

AI Legal Counsel / Investigative Guidance

• Systems like LAPIS could become more broadly used: AI providing legal reasoning support, helping officers decide on investigative steps, how to conduct interviews, what statutes or legal boundaries apply.  

• These systems could potentially reduce errors, but also raise questions about over-reliance and accountability.

Genetic & Phenotypic Prediction

• Use of AI to interpret more complex genetic data (beyond just face prediction) — like ancestry, health risks, or behavioral traits — might expand, though this is ethically and legally very controversial.

• AI could potentially assist in building more accurate composite images or profiles from DNA, but regulation and scientific validation are big hurdles.

Key Risks & Ethical Concerns

• Bias: Many AI systems (especially facial recognition) have higher error rates for people of color.  

• Privacy: Using AI for mass surveillance raises major civil liberties concerns.  

• False Positives / Wrongful Arrests: Over-reliance on AI matches without corroborating evidence can lead to mistaken arrests.  

• Transparency: Many AI models are proprietary (“black box”), making it hard to challenge their decisions in court.  

• Accountability: Who is responsible when AI is wrong — the software vendor, the law enforcement agency, or the individual officers?

• Regulation: There is no consistent national regulation in many countries; policies vary.  

• Ethical Use of Genetic Data: Predicting physical traits from DNA (phenotyping) treads into dangerous territory regarding privacy, consent, and potential misuse.

Bottom Line

• AI is already being used in serious crime investigations (including murders), especially for identification (facial recognition), forensic processing, and data analysis.

• More advanced and ambitious uses — like real-time crime detection, integrated investigative intelligence systems, and predictive models for criminal networks — are in development or being piloted.

• But significant caution is needed: the risks of bias, privacy violations, wrongful arrests, and lack of transparency are very real.

List of 10 Current Major Issues facing the US that Political Leaders need to address - Draft 2025

Here’s a list of 10 major issues facing the United States that political leaders ought to address. These are drawn from recent research and assessments of the current national situation. The initial list was generated by Chat GPT. Add your own major priorities to this list.

Economic pressure: inflation, cost of living & household affordability

• A large share of Americans say inflation remains a “very big problem.”  

• The affordability of health care has climbed sharply as a concern.  

• Political leaders need to address rising prices, stagnant wages for many workers, housing costs, and support for lower-income households.

Federal fiscal health & national debt

• National Debt and rising health care are flagged as “perhaps the greatest long-term threat.” The top 1% wealthy corporations and individuals could pay a one time trillion dollar tax and pay off the US National Debt, and still have trillions left over.

• The growing ratio of debt to GDP constrains government flexibility for policy, programs and future generations.  

Healthcare system & public health challenges 

• Affordability and access to universal healthcare are top concerns for the public.  

• The system needs reform for cost, access, preventative care, and public health infrastructure that must be strengthened.

Education, workforce readiness & inequality of opportunity

• Education is also a growing policy battleground for the US.  

• Gaps in educational outcomes, access to higher-skill jobs, and regional differences (urban vs rural) point to opportunity inequities.

• The US must invest in education, vocational training, and adapt to changing labour market.

Technological change, especially AI, and more effective regulation

• Emerging technologies (AI, robotics, quantum computing) are flagged as some of the biggest issues to watch for in the coming decade.  

• These raise questions of job disruption, privacy, fairness, bias, regulatory frameworks.

• Political leadership must develop smart governance for tech while preserving innovation.

Political polarization, governance and institutional trust

• Many surveys show concern about poor government leadership and an inability of the political system to work.  

• Broader institutional trust in media, government, etc. is also weak.

• Leaders need to rebuild trust, improve bipartisanship or at least functional governance, and strengthen democratic norms.

Infrastructure, resilience including climate & disaster vulnerability

• Insurance markets, disaster-risk, and infrastructure resilience are under pressure due to more frequent extreme climate disasters.  

• Aging infrastructure, under-investment and climate-related risks all compound the problem.

• Political leaders must invest in emerging infrastructure and build more resilience transportation, utilities, broadband, disaster readiness.

Immigration and demographic change

• Immigration, particularly illegal immigration, regularly appears among the top public issues.  

• Demographic shifts and aging population affect labour force, social services, and fiscal burdens as well.  

• Leaders must craft sustainable immigration policy, integrate newcomers, and plan for demographic change, e.g., older population.

Social equity, opportunity gaps & civil rights

• Issues of unequal opportunity—whether by race, region, socioeconomic status—remain central as the gap between the wealthy and workers grows..  

• Ensuring all citizens have access to education, healthcare, food and economic opportunity is key for social stability and fairness.

Global competitiveness, security & trade dynamics

• The U.S. is operating in a more contested global environment, i.e.technology, trade, diplomacy.  

• To maintain economic and strategic strength, U.S. leaders must better handle trade policy, alliances, technology leadership, supply-chain resilience.

• Domestic defense and trade policy intersects with foreign policy in important ways.

Why this list of priorities matters

• All of these issues are interconnected: e.g., economic pressure + workforce readiness + tech change → all affecting each other.They require long-term  strategy, not just short-term fixes.

• Many of these issues involve structural problems (debt, demographic change, climate, healthcare, education, technological infrastructure) will unfold over decades.

• Public sentiment surveys shows these issues matter to people—even if they prioritize them differently.

What other major issues and priorities should be added to the list above?