Category: AI Agents

AI Agents, Artificial Intelligence, Blockchains, cryptography, Uncategorized, Yogi Nelson

Understanding AI Safety: Global Initiatives Explored

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered!  Today’s question: is anyone working on artificial intelligence (AI) safety initiatives?  Let’s begin at the top—what is AI safety?

What is AI Safety.  According to IBM, AI safety involves ensuring AI systems are used responsibly, developed with human values, and that potential risks are identified and mitigated. It also includes safeguarding confidentiality and integrity of AI models, addressing bias, data security, and vulnerability to external threats.  AI safety should minimize potential harm to human and the environment, as well as prevent misuse and other unintended consequences.  

AI Safety Institutes Across the Global.  While researching this topic, I discovered the existence of numerous AI safety initiatives and institutes on every continent.  Some are government dominated, others industry led, and you can also find AI safety institutions within the non-profit/research eco-system.  Today, I’ll highlight a few AI safety initiatives and institutes from every continent.  Where to start?  Why not in alphabetic order with the African continent.

AI Safety Initiatives in Africa.  For better or worse, there is no unified AI safety initiative coming out of Africa, as a continent.  However, that doesn’t mean individual African nations are asleep.  To the contrary, several African nations have active AI safety programs.  For example, Nigeria has a draft national AI strategy in circulation that includes AI safety.  https://paradigmhq.org/wp-content/uploads/2021/11/Towards-A-Rights-Respecting-Artificial-Intelligence-Policy-for-Nigeria.pdf   Or for instance, in Egypt the National Council for Artificial Intelligence, a government think tank, produced the following report on AI that includes AI safety.

Click to access AIstrategy%20English%2016-1-2025-1.pdf

Numerous other African nations have strong initiatives but for now we move on to Asia.

AI Safety Initiatives in Asia.  It’s unrealistic to expect that Asia would be limited to only one umbrella organization dedicated to AI safety.  Asia is to diverse and enormous of the continent for that.  Nevertheless, there are regional blocks of nations working in collaboration to ensure safe AI.  A prime example is Artificial Intelligence Safety Asia, AISA.  AISA is a global non-profit dedicated to the international governance of safe AI by Asians, starting in Southeast Asia.  Their goal is to build local expertise and foster collaboration in order to produce practical AI safety policies.  AISA accomplishes the mission by training civil servants, forging partnerships, and “incubating” junior researchers.  https://www.aisafety.asia/

To no surprise, Singapore has a major AI safety institute; it’s known as Artificial Intelligence Singapore Institute (AISI).  AISI has several AI safety initiatives underway, including an extensive multi-year effort with the Digital Trust Centre Singapore (DTC) and the Infocomm Media Development Authority of Singapore (IMDA) for the purpose of advancing AI safety in Singapore.  https://sgaisi.sg/

AI Safety Initiatives in Europe.  Europe has a plethora of AI safety initiatives, and one of those is the European Network for AI Safety, ENAIS is its acronym.  ENAIS is a think tank of researchers from across Europe united in the effort to advance safe AI use.      https://www.enais.co/

AI Safety Initiatives in North America.  The U.S. government has an AI safety institute; it’s called the U.S. AI Safety Institute (US AISI).  The mission is to identify, measure, and mitigate the risks of advanced AI systems, says USAISI.  The idea is to harness the enormous potential of AI technology by developing the testing, evaluations, and guidelines required to accelerate trustworthy AI innovation–with a keen focus on helping to prevent misuse by those who seek to undermine public safety and national security.  https://www.nist.gov/aisi

AI Safety in South America.  According to a recent study by the Brookings Institute, a think tank in Washington, D.C., regional cooperation in the field of AI safety is emerging in Latin America.  Brookings notes that Brazil, Peru, and Costa Rica, are all using existing AI safety models from Europe, North America, and Asia as well as their own ideas to create AI safety standards in their respective nations.  https://www.brookings.edu/articles/regional-cooperation-crucial-for-ai-safety-and-governance-in-latin-america/

Problem solving begins with recognition that a problem exist, or may soon appear.  Its encouraging to see a concerted effort across the global working on AI safety.  Time to say goodbye with the World Economic Forum’s motto: “entrepreneurship in the global public interest”.  Lol. 

Until next time,

Yogi Nelson

AI Agents, Artificial Intelligence, Blockchains, content creation, cryptography, Uncategorized, Yogi Nelson

How Personality Traits Shape AI Attitudes

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered.   Benjamin asks, do personality traits influence attitudes toward artificial intelligence?

Benjamin that’s an awesome question!  To answer your question, I’ll start by defining personality traits. 

Personality Traits.  ScienceDirect tell us that personality traits are relatively stable patterns of thoughts, feelings, and actions in which each individual is different from the others. In other words, personality traits are fairly stable over time and across situations but still open to change. Personality traits are primarily units of analysis of individual differences relative to cognitions, emotions, motivations, and behavior. They do not include physical features, e.g., attractiveness, or abilities, e.g., intelligence.

Personality traits operate within a larger social context.  Hence, the place to begin is obvious—economic.  Let’s be honest, AI makes workers anxious—and workers may have reason to be nervous.  According to Goldman Sachs, McKinsey, and the Nexford University, between 400M and 800M workers worldwide could lose their jobs by 2030 due to AI.  Jobs most at risk include:

Data Entry                                           Customer Service Representative

Manufacturing                                    Transportation & Logistics

Retail Sales                                          Market Research Analyst

Proof Readers & Translators              Radiologists and Diagnostic Technicians

Financial Analysts                               Bookkeepers and Accounts

Economic is not the exclusive concern of humans with AI; people also express worry about the social impact of AI.  For example, will AI reinforce biases?  Will AI leave millions “behind”?  Will AI eliminate all privacy?  Will AI cut my health insurance right before an illness?  The list of concerns is long.

According to “The Role of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes Toward Artificial Intelligence, Journal of Human-Computer Interaction, 2024,” personality traits influence attitudes toward AI. The report is based on a survey taken in Turkey.  Let’s examine the report in detail.

https://www.tandfonline.com/doi/pdf/10.1080/10447318.2022.2151730

The following hypotheses were tested:

  1. Demographic Characteristics (i.e., age, gender, education level, level of computer usage, level of AI) could predict attitudes towards AI.
  2. Higher openness to experience would coincide with greater positive attitudes toward AI.
  3. Higher AI anxiety would predict more negative attitudes toward AI.

RESULTS

Age. Age did not predict attitudes toward AI.  That was somewhat unexpected. 

Agreeable.  Researchers used a series of questions to determine whether agreeable traits.  Researchers concluded people who were determined to be agreeable had positive attitudes toward AI.  Interesting! I suppose I should agree. lol.

AI Configuration Anxiety.  AI configuration anxiety means a fear of humanoid AI, e.g., human-like robots.  The more AI configuration anxiety, the more negative attitude toward AI. Logical.

AI Learning Anxiety.  AI learning anxiety significantly predicted both positive and negative attitudes toward AI.  The less learning anxiety the more positive attitude and vice versa.

Computer Usage. Computer usage was predictive of attitudes toward AI.  The more computer usage the greater was the positive view of AI. No surprise.

Conscientiousness.  Whether people are conscientious or not apparently makes no difference in their attitude toward AI, researchers say.

Extroversion.  The findings were mixed on extroversion.  Technologies that facilitate social interactions may be liked by extroverts but AI technologies can help reduce social interactions.  Thus, the mixed results.

Gender. Gender did not predict attitudes toward AI. However, men tend to view AI more positively than females. 

Job Replacement Anxiety.  People are worried.  Lol.

Self-Rated AI Knowledge.  People who consider themselves tech savvy and AI literate, have a more positive attitude toward AI.  Makes sense.

Time to end with a proverb from Turkey, where they say: “stretch your foot according to your blanket”.

Until next time,

Yogi Nelson

AI Agents, Artificial Intelligence, Blockchains, Environment, Productivity, Railwlays, Uncategorized, Urban Planning, Yogi Nelson

Navigating AI Disruption in the Railway Sector

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered.   Harold asks, how will artificial intelligence affect the railway industry?

Harold, you came to right place.  I’ll answer your question by citing research reports from McKinsey & Company, International Union of Railways (UIC), and Startus Insights.  Let’s start with the McKinsey report, titled: The Journey Toward AI-Enabled Railway Companies.

Prominent AI Use Cases in the Railway Industry:  McKinsey Report Findings

According to McKinsey, railway companies are focusing their AI efforts on approximately 20 use cases.  It should be noted, the McKinsey identified over 100 potential use cases!  The top 20 use cases are related to four key performance indicators:  on-time performance, customer engagement, safety, and operational performance.  The table below summarizes the use cases by category:

Table 1
ARTIFICIAL INTELLIGENCE USE CASES IN THE RAILWAY INDUSTRY
Business ActivityDescriptionAI Use Case
Railway UndertakingsActivities that are directly & indirectly related to delivering the final productCrew trainingSafetyOnboard operationsRolling stock maintenanceTrain station operationsRolling stock procurement & inventory management
Infrastructure ManagementActivities that are directly & indirectly related to the infrastructure needed to deliver the final railway productNetwork planningNetwork traffic managementNetwork constructionNetwork maintenance Rail safetyNetwork procurement and inventory management
Passenger ExperienceCustomer facing activities related to the operations of the railway companyBooking and ticketingCustomer railway journeyPassenger informationIn-station additional revenue  
Support FunctionsEssential non-operational activitiesHRFinanceIT

Of course, not all use cases have equal priority.  In the table below, the five most common use cases are listed on the left, and the five least used on the right.  The other 10 are in the middle.

Table 2 ATable 2B
Top 5 AI Use Case in Railway IndustryBottom 5 AI Use Cases in Railway Industry
Crew and shift managementNetwork infrastructure digital twin
Rail predictive maintenanceReal time disruption management
Real time intermodal informationTalent training
Energy efficient managementAutonomous trains
Security fraudSoftware development

The Keys to Successful Incorporation of AI in the Railway Industry:  UIC Report

We now turn to the findings by the Union of International Railways; UIC per their French acronym.  The UIC researchers claims that the railways with the most successful AI abilities share certain characteristics. For example, these railway companies dedicate research and development teams to their AI efforts.  Furthermore, they establish cultures of innovation and investment in partnerships to develop new technology.  Yet a third reason is that they build capabilities to implement use cases; and take a business-driven approach (rather than solely relying on IT departments) to drive development.  UIC researches say, there are six specific keys to success: strategic roadmap, skills, agile operating model, technology, data, and adoption and scaling. 

Who Are the AI Disrupters in the Railway Industry:  StartUs Insights Report

According to StartUs Insights, a consultancy specializes in discovery of intelligence trends, innovation, and engagement with the world’s most promising startups, scaleups, and technologies, there are 20 AI startups impacting the railway industry.  I’ll refrain from listing them all, and instead highlight three that best exemplify the AI story in railways. 

Let’s start with rail safety and the startup called RMT.  RMT is based in Italy.  RMT specializes in automatic recognition of defects on rail infrastructure, and employing AI to detect physical defects.  Energy efficiency is the wheelhouse of RailVision Analytics, a Canadian startup dedicated to improving energy efficiency via algorithms that reduce unnecessary braking, throttles, and train handling adjustments.  Last, there is Cervello.  Cervello is an Israeli startup. Cervello says it provides railways with “… comprehensive security solutions and in-depth visibility of the operational network and infrastructure.” With Cervello misleading commands are identified.  Moreover, Cervello produces a contextual view of the affected assets and operational impact.

Time to go but not before ending with this famous lyric from the O’Jays:  …” People from all over the world join hands start a love train, love train …”

Until next time,

Yogi Nelson

AI Agents, Artificial Intelligence, Blockchains, climate-change, cryptography, Environment, Uncategorized

How Blockchain Can Drive Chile’s Renewable Energy Transition

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered!   As a bonus, a proverb is also included.  Today’s question comes from Fernando in Santiago de Chile, and he ask if blockchain technology can aid Chile in its transition to renewable energy?

Fernando, you came to the right place.  This is an excellent question.  I thought to myself what institution is likely to investigate this issue; thus while traveling through Chile recently I found a research paper from the World Bank titled, “Using Blockchain to Support the Energy Transition and Climate Markets:  Results and Lessons from a Pilot Project in Chile”.   Let’s go over their findings, but first a word about blockchains.

What is a Blockchain: A blockchain is a shared ledger of transactions between parties in a network, not controlled by a single central authority. One can think of a ledger like a record book: it records and stores all transactions between users in chronological order. Instead of one authority controlling this ledger (e.g. bank), an identical copy of the ledger is held by all users on the network.  Let’s examine how blockchain technology can play a part in Chile’s energy policy as it transitions from carbon-based energy and facilitates market solutions to climate change challenges.

Global Energy Transition: According to World Bank researchers, humans are racing towards renewable energy solutions.  The International Energy Agency, reports renewables account for 13% of the energy market; an increase of 24% since 2017.  However, the more insightful statistic is that from 2017 – 2024 renewables produced 70% of the global growth in electricity generation, led by solar photovoltaic and followed by wind, hydropower, and bioenergy. Why?  Industry expert say the accelerated pace of renewable energy sources is the consequence of both concern over climate change and the increased rate of technological innovation in the industry.  

Chile’s Renewable Energy Policy: Chile aspires to be a global leader in international climate policy.  The government has committed to phase out coal by 2040 and move toward carbon neutrality by 2050. Chile is on target to meet its commitment of generating 45% of all electricity from renewable sources.  Nice! However, Chile has more room to run.  In fact, some estimations suggest that by 2030 up to 75% of electric power generation in Chile could come from renewable sources. The energy transition—and the use of market instruments— may be the key to accelerating Chile’s emissions reduction targets. Chile is also exploring the development of a strategy for participating in integrated carbon markets.

Chile’s Renewable Energy Pilot Program:  Chile’s Ministry of Energy created the Public Solar Roofs Program to support the installation of PV systems in public buildings.  The objectives were to reduce the cost of operating public buildings, stimulate the market for PV solutions through the installation of solar panels, and generate free public access to information on the costs and conditions of PV projects aimed at self-consumption. Its objective was to test a blockchain-based system of certification for renewable and emissions reductions. The project installed hardware and developed a blockchain algorithm designed especially for DER installations. To validate data, project managers used a measurement system independent of the generation plant, which read multiple climatological variables, including solar irradiation. The blockchain platform records the following information:

• Geolocation in Universal Transverse Mercator coordinates

• Time stamp using Coordinated Universal Time

• Environmental data (radiation and ambient temperature)

• Electricity generation (obtained from the billing meter or data acquisition system) • Identification of the PV facility

• Media Access Control (MAC) address of the facility (unique identifier of the network device).

RESULTS: The pilot helped strengthen and develop the market for small-scale renewable energy generation, which has had difficulties taking off, by creating additional incentives through the potential sale of climate assets. The authors noted that although there are benefits to blockchain technology, scalability and replicability remain a challenge. Last, the project developed and generated a shared ledge system of relevant energy generation and emission reduction data.

Fernando, I hope you enjoyed this article about what your country’s transition to renewable energy.  I say goodbye with a proverb from Chile, “words are like the wind, they can carry good or bad seeds”.

Until next time,

Yogi Nelson

AI Agents, Artificial Intelligence, cryptography, Uncategorized, Yogi Nelson

AI in Healthcare: Key Findings from Recent Research

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   As a bonus, a proverb is also included.  Today’s question, submitted by Doctor Vargas of Manati, PR, and she wants to understand what academic researchers in the field of health care are say about the use of artificial intelligence.

Doctor Vargas, you came to the right place.  There has been an explosion in research related to AI in health care. I have an answer to your question based on an article titled, Artificial Intelligence in Healthcare Institutions: A Systematic Literature Review on Influencing Factors by Roppelt, Kanbach, and Kraus, 2024 in a scholarly journal called, Science Direct.  Time to examine what the literature says. https://www.sciencedirect.com/science/article/pii/S0160791X23002488

According to the researchers, the global health system is facing serious challenges.  They cite the growing number of patients due to population growth, increased prevalence of chronic diseases, increasing healthcare costs, and staff shortages.   The good news is AI has the potential to solve some of the challenges ahead, claim the authors.  The researchers say, “… AI is a technology that, through rules-based logic, can help to significantly speed up the process of analyzing vast amounts of data and leverage patterns by mimicking human intelligence.  AI may result in fast and often better-advised decisions. Thus, as it pertains to the healthcare industry, AI has the potential to overcome staff shortages in developing and developed countries, enhance organizational efficiency, and maximize diagnostic accuracy as well as patient outcomes by providing at least comparable results in terms of quality compared to human based assessments. Consequently, Al may reduce costs due to avoidance of inefficiencies, unnecessary treatments, and late diagnoses.

THE UNIVERSE OF LITERATURE REVIEWED BY THE RESEARCHERS

Researchers discovered approximately 1,100 published articles on the topic since 2023.  However, after analyzing the universe of literature in greater detailed soon learned only about 130 were truly on point.  The authors also found that most studies were published in journals related to information technology, not medicine, or journals dedicated to the nexus of AI and medicine.  Nearly 60 % elaborate generally on the factors influencing AI adoption in the healthcare industry, with the US at the high end of the spectrum.  AI seems to be most widely adopted in cardiology and radiology and rather at an early stage in dermatology and psychiatry.  Interesting that there are not many studies of AI in medicine in business management journals.

FACTORS THAT INFLUENCE AI ADOPTION IN HEALTHCARE:  THE FINDINGS

Macro-economic readiness. The research at Science Direct found that macro-economic readiness is mainly driven by governments.  For example, the research say adequate IT infrastructure, e.g., access to smart devices for the population and energy adequacy, especially for remote areas and certain populations.  Also of interest is the role played by “AI communities.”  The notion is that when there are established partnerships, collaborations, etc. the network effects kicks in and the impact is exponential. 

Technological readiness.  Researchers are finding that technological readiness depends on three factors: 

  • The importance of overcoming algorithmic challenges.  What type of algorithmic challenges?  Many, including lack of data, and/or inferior quality, etc.
  • Provide a compelling, multi-faceted value proposition.  The most obvious are clearly added value in the form of efficiency, user-friendliness, adherence to data-privacy regulations, interoperability, and the ability to tailor the application to individual needs.

Regulatory readiness.  Essentially, the authors are suggesting close collaborations with regulators.  The author point to three key issues:  political support, clarification of legal questions, and establishment of regulations. As a former government regulator, this is sage advice but not easy to execute because contrary to popular belief the “government” is not a unified organism.

Organizational readiness.  A failure to plan is a plan to failure, say the authors hence the reason they strongly recommend to prepare the organization before implementing an AI health care system or be prepared to fail.  The researchers break down the steps into four steps:  prepare an organizational strategy, develop a supportive organizational culture, clear tasks and assignments, and an adequate IT setup.

User readiness. Recognizing that organizations consists of people, the researchers says users are at the center.  Furthermore, researchers conclude four facts are the key to user readiness:

  • Awareness:  in other words, do users know the technology exist?
  • Beliefs:  do users believe the technology will work? 
  • Personal innovativeness:  are users willing to try something new?
  • The financial situation of the individual: 

Doctor Vargas, now you know what the literature says.  I hope this helped.  I end with a proverb from Mexico:  in the absence of love, some tacos al pastor will do.”

Until Next Time,

Yogi Nelson