AI Revolution: Unveiling Its Power Across Key Industries

By now, we’re all familiar with Bard, ChatGPT, MidJourney, and all the other AI bots available to users. There are even dark web AI bots out there now.

Article by
Becky Chase
Article date
October 27, 2023

Why managing AI risk presents new challenges

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The difficult of using AI to improve risk management

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How to bring AI into managing risk

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Pros and cons of using AI to manage risks

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Benefits and opportunities for risk managers applying AI

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AI is becoming more and more integrated into our daily lives, sometimes we’re not even aware of its presence or impact. From helping doctors diagnose diseases to making your Netflix binges more enjoyable, AI is reshaping our world. Here's how.

AI in Healthcare: Beyond the Stethoscope

  • Diagnostics: Machine learning models can help identify diseases from medical images, genomics, and other data.
  • Treatment Recommendations: AI can suggest treatment plans based on patient data.
  • Drug Discovery: AI expedites the process of drug discovery and optimization.
  • Predictive Analytics: Predicting patient readmissions, potential outbreaks, and other healthcare trends.
  • Precision Medicine: Tailoring Treatment to Every Individual

    The ability of Doctors to treat and accurately diagnose and provide proper treatment has greatly improved with the development of gene editing, targeted therapies, optimization trials, and personalized treatment plans. AI can analyze a patient's records including past records, data, and family history, and provide a tailor-made treatment plan. AI has been used to identify the best candidates for clinical trials, as well as analyze tumor genomes, and predict the outcome of gene editing technologies. The list of AI + Medicine = Precise and Personalized healthcare goes on and on, so for now, let’s move on to Robot AI.

    Robot-Assisted Surgeries: Enhancing Precision and Minimizing Invasiveness

    AI and robotic systems have made remote surgeries possible. A surgeon in one location can operate on a patient in a different location using robotic systems, guided by real-time data and high-definition visuals. Robot-assisted procedures, such as the da Vinci Surgical System, allow surgeries to be performed through small incisions, leading to faster recovery, reduced hospital stays, and minimal scarring.

    AI-powered simulators are used for training surgeons on robotic systems, providing a realistic environment without the risks associated with real-life surgeries. During actual procedures, AI can guide less experienced surgeons, suggesting optimal maneuvers or highlighting potential concerns.

    Robots, when combined with AI, can execute surgical maneuvers with a level of precision that surpasses human steadiness. The AI can help in making minute adjustments that account for physiological nuances, thereby reducing potential surgical errors.

    While AI-enhanced robot-assisted surgeries offer numerous benefits, there are challenges, including the high costs of robotic systems, the need for specialized training, and potential technological malfunctions. Ethical considerations arise when discussing the responsibility for surgical outcomes. Determining accountability between the AI system, the robot, and the surgeon can be complex.

    AI-Powered Diagnostics: Catching Diseases Before Symptoms Arise

    AI-powered diagnostics is a burgeoning medical field, using algorithms and machine learning to detect and diagnose diseases often long before symptoms are apparent to patients or clinicians.

    Deep learning algorithms can analyze X-rays, MRIs, CT scans, and other imaging modalities to identify patterns or anomalies indicative of diseases like tumors, fractures, or infections. AI systems can detect abnormalities with high accuracy, sometimes surpassing human radiologists.

    AR, combined with AI, can overlay diagnostic information onto real-time imagery. For example, during surgery, it might highlight areas of concern or provide real-time data analytics.

    With the increased use of AI in diagnostics, ensuring patient data privacy is paramount. There's a risk that with highly sensitive AI tools, benign conditions might be overdiagnosed or misinterpreted as serious conditions, leading to unnecessary treatments.

    Transforming Finance with AI: Smart Money Moves

    Fraud Detection: Real-time Anomaly Spotting

    AI has become a powerful ally in the fight against fraud across various industries, enhancing traditional methods with predictive capabilities and real-time analysis.

    Detecting anomalies, predictive analysis, and reducing false alarms are all ways AI is helping the finance industry now.

    AI models can learn typical transaction patterns and flag unusual or unexpected activities. For example, if someone usually shops locally and suddenly makes a high-value purchase in a foreign country, AI can detect this irregularity.

    As AI systems evolve, so do the tactics of fraudsters. They might try to "poison" the AI model by feeding it false data to reduce its effectiveness.

    Algorithmic Trading: Maximizing Profits Through Data Analysis

    Traditionally, algorithmic trading was based on preset rules defined by humans. For example, if stock X drops by Y%, then buy Z shares. With the inclusion of AI, these strategies have become much more dynamic and adaptive.

    AI models might become too tailored to historical data and perform poorly in real-world scenarios. There are concerns that HFT and certain algorithmic strategies can manipulate market prices. Over-reliance on automated systems could lead to significant financial losses if there's a system malfunction or if algorithms make unexpected decisions during market anomalies. Many countries are looking into or have already implemented regulations to oversee and control algorithmic and HFT trading due to concerns about market stability and fairness.

    Personal Financial Assistants: Smart Saving and Investment Recommendations

    By combining vast amounts of financial data with machine learning algorithms, these virtual assistants provide tailored financial advice and insights. By combining vast amounts of financial data with machine learning algorithms, these virtual assistants provide tailored financial advice and insights.

    AI can categorize and track expenses, providing a clear picture of where money is being spent. By analyzing spending habits, these systems can offer personalized budgeting advice, suggesting where cuts can be made or where spending is excessive.

    AI-driven tools can analyze an individual's risk tolerance, financial goals, and market conditions to suggest suitable investment opportunities. They can also constantly monitor the market and provide real-time advice on when to buy or sell certain assets.

    AI on the Move: Transportation Innovations

    Autonomous Vehicles: The Road to Self-Driving Future

  • Sensors and Perception: Self-driving cars are equipped with a range of sensors like LIDAR, cameras, and radar. These help the vehicle perceive its surroundings. AI processes this data in real time to detect and classify objects, pedestrians, and other vehicles.
  • Decision Making: Once the environment is understood, AI determines the best course of action, be it changing lanes, braking, or accelerating.
  • Control: After deciding on an action, AI systems send commands to the vehicle's control systems.
  • Safety and Testing: Through simulations, autonomous vehicles can "drive" millions of miles in virtual environments, ensuring that they can handle various scenarios safely.
  • Connectivity: Vehicles communicate with each other and infrastructure (V2X communication), enhancing traffic flow and safety.
  • Traffic Management: Predicting and Preventing Jams

  • Traffic Prediction: Using historical and real-time data, AI can predict where traffic congestion might occur.
  • Adaptive Traffic Light Control: AI algorithms can adjust traffic light timings based on traffic flow, reducing wait times and congestion.
  • Accident Response: Quick detection and response to accidents can be automated, notifying emergency services and rerouting traffic.
  • Infrastructure Maintenance: Predictive analytics can foresee infrastructure issues, such as road damages, enabling timely repairs.
  • Optimized Logistics: Streamlining Supply Chains with Predictive Analysis

  • Demand Forecasting: AI can predict demand for products, enabling optimized inventory management.
  • Route Optimization: For deliveries and shipments, AI can find the most efficient routes, considering factors like traffic, weather, and fuel consumption.
  • Warehouse Automation: Robots, guided by AI, can pick, pack, and sort products more efficiently.
  • Predictive Maintenance: AI can predict when vehicles or machinery will need maintenance, reducing downtime.
  • Entertainment: Content Creation and Customized User Experiences

    Open up a streaming service, Netflix, YouTube, or maybe Spotify… all of these top platforms use AI to help cater recommendations to users.

    Netflix for example, uses AI to compare various user’s watch lists to find patterns. These patterns are used to recommend these shows to other users with similar watched titles. The AI uses attributes like genre, director, actor, etc. Occasionally, it will be used for A/B testing for thumbnails of shows. For example, it can gather analytics like how long someone hovers on a title or how often someone clicks a specific thumbnail.

    YouTube does a similar thing, using AI to calculate engagement, watch time, etc. to recommend videos and cater their recommendations. However, recently there’s been a lot of talk about how weird YouTube’s recommendations have been. Personally, I have been experiencing some very strange and unrelated recommendations on my YouTube home page. One of the more specific instances is, it’s been recommending videos I’ve already watched. Typically those would appear in the “Watch it Again” section, but these have been popping up in my regular recommended section.

    Spotify’s AI, along with its pattern-finding scanning, also analyzes audio. It analyzes tempo, instrumentation, and rhythm to better understand what users like, similarities, etc. to better recommend songs and albums.

    Video game developers have been using AI for quite some time. Adaptive NCPs, procedural generation, and dynamic difficulty have been around for a minute. Motion capture and animation, personalized gaming experiences, game testing, and player behavior analysis are newer. AI bots are used to assist in testing and finding solutions to bugs and areas where players may get stuck. Game developers are also using AI to monitor and identify patterns in how players interact and engage with the game, this data is then used to create and strategize more effective gameplay in the future.

    TLDR: a few ways AI impacts your daily entertainment:
  • Content Recommendation: Platforms like Netflix and Spotify use AI to suggest shows, movies, and music.
  • Video Game Design: AI-driven non-player characters and game development tools.
  • Automated Video Editing: AI tools that assist in video creation and editing.
  • Conclusion:

    The transformative power of AI is undeniable, weaving its intricate web across diverse industries, from healthcare and finance to entertainment and transportation.

    Its potential is vast, ushering in innovations and enhancements that were once the stuff of science fiction. From revolutionizing patient treatments to optimizing financial strategies and crafting tailored entertainment experiences, AI's footprint is ever-growing. As we stand on the cusp of a technological renaissance, it's imperative for professionals across all sectors to remain abreast of AI advancements.

    Nexrage is currently working on implementing Artificial Intelligence to assist our clients. We’re using many of the instances detailed above in our digital wallet client.

    By understanding and harnessing its capabilities, we not only shape our industries but also pave the way for a future that's smarter, more efficient, and infinitely promising.

    Stay curious, stay updated, and let's journey into this AI-driven future together.

    AI: Shaping Tomorrow's Industries Today

  • Smart Grids: Optimizing energy distribution based on demand predictions.
  • Predictive Maintenance: Foreseeing when components of energy infrastructure might need maintenance.
  • Energy Consumption Forecasts: Predicting energy needs for better grid management.
  • Real Estate:
  • Price Optimization: Predicting property prices based on historical and current market data.
  • Virtual Tours: AI-powered VR experiences of properties.
  • Predictive Maintenance: Identifying when parts of a building might need repairs.
  • Education:
  • Personalized Learning: Adapting content to fit individual student needs.
  • Automated Administration: AI-driven systems for student attendance, grading, etc.
  • Virtual Tutors: AI-powered platforms offering tutoring in various subjects.
  • FAQ Section:

    Q: How is privacy maintained with the use of AI in healthcare?
    A: AI solutions in healthcare typically utilize anonymized data, with strict regulations ensuring patient confidentiality. Advanced encryption and data security measures further protect sensitive information.
    Q: Can AI completely replace human roles in finance?
    A: While AI can automate and enhance certain tasks, the human touch remains essential, especially in areas requiring complex judgment, emotional intelligence, and ethical considerations.
    Q: How close are we to a world dominated by autonomous vehicles?
    A: While significant strides have been made in autonomous vehicle technology, widespread adoption requires further advancements, regulatory approvals, and public acceptance. We're on the path, but there's still a journey ahead.