Category: Artificial Intelligence

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

Artificial Intelligence, Banking, Blockchains, cryptography, International Finance, Uncategorized

GENISUS Act: Implications for Stablecoin Issuers

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your questions are answered!   As a bonus, a proverb is also included.  Today’s question comes from Latasha and she asks what is the GENISUS Act?

The GENISUS Act is a proposed federal law, introduced by Senator Hagerty of Tennessee–your home state.  To no surprise, GENISUS is an acronym: “Guiding and Establishing National Innovation for U.S. Stablecoins, 2025.” (Feds have the best acronyms!  Lol.)  Let’s review GENISUS Act section-by-section, beginning with definitions.

GENISUS defines 23 terms but none more important than Payment Stablecoin. According to GENISUS, a payment stablecoins is a digital asset that is designed to be used as a method of payment/settlement, and which the issuer is obligated to convert, redeem, or repurchased for a fixed amount of monetary value and represents it will maintain or creates the reasonable expectation that it will maintain, a stable value relative to the value of a fixed amount of monetary value, and is not a national currency or a security issued by an investment company.” We now move on to Sections 3 – 7.

Permitted Stablecoin Issuers:  If GENISUS becomes law only a permitted stablecoin issuer can issue stablecoins.  No free lancers permitted!  Don’t even consider it unless you enjoy living in a 6 x 9-foot prison cell with a dude name Buba!  Lol.

Requirements for Issuing Payment Stablecoins. There are a litany of requirements to issue a payment stablecoin.  Below are a few highlights of what issuers must do:

  1. Maintain reserves backing the issuer’s payment stablecoins outstanding on an at least 1 to 1 basis comprising of: U.S. Dollars, demand deposits held in U.S. banks, treasury bills, notes, and bonds of 93 days or less, repurchase agreements of seven days or less, money market funds, Central Bank reserve deposits.  In other words, liquid reserves that are 1-to-1. 
  2. Issuers must also publicly disclose their redemption policy, establish procedures for redemption, and publish monthly composition of the issuer’s reserve. Disclosure!
  3. Monthly compliance certificates from the issuers, CEO and CFO.

Limitations of Stablecoin Activities.  Stablecoin issuers are limited to the following activities:

  • Issue payment stablecoins
  • Redeem payment stablecoins
  • Manage related reserves
  • Provide custodial or safekeeping services for payment stablecoins
  • Other directly related work.

Stablecoin Regulators.  GENISUS does not establish a new federal stablecoin regulator.  Relief! Consequently, if a nationally chartered bank, e.g. Bank of America, issues a stablecoin the same federal banking regulator, Office of the Comptroller of the Currency, (OCC) that supervised Bank of America for safety and soundness, will be tasked with regulating the bank’s stablecoin operations.  Simple.  The same applies if the bank has a FDIC banking charter.  State chartered banks can issue stablecoins, provided their corresponding state banking regulators follows the GENISUS Act. Standard practice in banking.  What if a federal qualified nonbank wants to issue a stablecoin you ask?  OCC will be the regulator of those nonbank stablecoin issuers.  Let’s move on.

Application and Approvals.  From the date the stablecoin regulator deems the application complete, the applicant must be approved or denied within 120 days.  The catch is from the date the application is deemed complete.  A malicious regulator can string an applicant along with a constant request for additional information. 

If the regulator deems the application unsafe it can reject the application but it must explain with specificity, including all findings made by the regulator with respect to all identified material shortcomings in the application, including actionable recommendations on how the applicant could address the identified material shortcomings.  I find this last section unusual and troublesome.  Essentially GENISUS requires the regulator to explain to the applicant how to do their “homework”.  This is problematic.  Afterall, if an applicant is incapable of preparing a coherent application, doesn’t it portent an institution incapable of running the program effectively?  I think so.  Moreover, if the stablecoin issuer fails, will it blame the banking regulator for its failure given the issuer could reasonably claim it followed the regulator’s instruction? 

Rulemaking.  Did you know that when Congress passed a law it writes into the law a section titled rulemaking?  The purpose of this section is to authorized and require the executive branch to write the regulations necessary to implement the letter and spirit of the law.  In the case of GENISUS, Congress directed the various stablecoin regulators to issue the regulations within 180 days from the day GENISUS becomes law.  Regulators, you better step on the gas!

Time for me to make a genesis appearance at my next engagement but before I go, I leave you with this proverb from Turkey: “a hungry bear does not dance”.

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains, cryptography, Germany, Uncategorized

Latest Trends in Crypto Key Management: Insights from Germany

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain technology questions are answered!  As a bonus, a proverb is also included.  Today’s question comes from Wolfgang in Stuttgart and he wants to know what is the latest in crypto currency key management from Germany?

Wolfgang, you came to the right place.  I understand why you would ask this question and its importance.  After all, as often said in the crypto world, “not your keys, not your crypto!”.  With that in mind I drove deep into academic research for the latest findings.  I discovered an article titled, “Perceptions of Distributed Ledger Technology Key Management – An Interview Study with Finance Professionals”, Guthoff, et al, 2023, Helmhotz Center for Information Security, Germany.  Their paper is focused on key management for financial institutions not individuals, nevertheless it is fascinating to learn what the BIG BOYS & GIRLS are thinking. .https://publications.cispa.saarland/3948/1/guthoff2023keymanagement.pdf

RESEARCH BACKGROUND AND METHODOLOGY:  The researchers focused their attention on private key management within the traditional financial sector (trad-fi) and the cryptocurrency space (de-fi).  By incorporating the views and perspectives of employees working in trad-fi and de-fi, the unique perspectives of the established and newer financial institutions were both included. Nice!  In section two, the authors define a number of essential terms readers must understand to completely comprehend the findings.  Below are two examples of terms that were defined:

Key Management:  the activities involving the handling of cryptographic keys and other related key information during the entire life cycle of the keys, including their generation, storage, establishment, entry and output, use, and destruction. According Guthoff, key management is a combination of different key-related aspects, including key usage and storage.  Guthoff explains further that the goal of key management is to generate, store, distribute, use, and revoke cryptographic keys (integrated into enterprise processes) while keeping the private key secret. Key Management is not necessarily equal to a (cryptocurrency) wallet, but a wallet may be used as a simple tool for key management.

Custodial Key Storage: is the storage of keys by a separate party, which can be either in-house or a third entity that does not use the key. This party can, but does not have to, take care of all other aspects of KM. For self-managed assets, this could be a cryptocurrency exchange. For financial institutions, custodial key storage can be implemented in-house or externally by an intermediary.

Research Findings:  Essentially, the threats to key management fall into four different categories: internal, external, systems and infrastructure, and force majeure.  Force majeure means unforeseeable circumstances.  Unfortunately, the research paper covers too many findings for me to discuss them all; hence, instead I’ll give you just a few highlights.

Multi-signature keys:  Multi-signature keys were a hot topic among respondent and participants were enthusiastic about the concept.  According to the survey participants the two main benefits of this technique were resilience against key loss or compromise and added protection against malicious employees. Some participants also proposed storage of keys at a bank or a notary as a backup option.

Invisible Key Usage. The invisible key usage pertains to trad-fi but has implications for de-because management of private keys definitely holds back mass adoption.  In the view of the survey participants, they preferred a solution where key usage is mostly encapsulated within an application and hidden away from the user.  Although participants were referring to enterprise systems, the principle applies–the risk of losing a key through an attack or intended malicious actions by an employee.  Participants thought usage of the key is best through access via personal credentials like username and password or multifactor authentication, using a phone or biometric features.

CONCLUSION:  Bad news–researchers are skeptical whether existing key management systems can function effectively at the enterprise scale.  They say efforts to maintain on-chain authentication and audit functionality covering day-to-day operations, e.g. employee absence or shifting responsibilities within the organization – as well as – contingencies such as key compromise or force majeure events – is unmanageable, except for the smallest institutions. 

Time to say goodbye with a proverb from Germany: “one becomes wise through damage”.

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