Humans are the noblest of all creations, but they are not invincible. Natural calamities, like tsunamis, earthquakes, floods, storms, droughts, and wildfires, show the vulnerabilities of humans. Likewise, outbreaks like plagues, Black Death, smallpox, flu, HIV, and COVID-19 also affect humanity to the greatest extent. While these catastrophes are not created by humans, some are manmade. The technology that humans create poses unparalleled risk to their existence – this is the risk that can make us extinct or cause some type of adversity that limits our ability to grow and thrive enduringly. For example, the creation of the atomic bomb posed a high level risk to our existence, and after this invention the humans have only increased problems for themselves. It is difficult to estimate the exact percentage of existential risk to humans; rough estimates indicate that existential risk due to nuclear war and climate change is approximately. 0.1%. The chances of an outbreak causing the same type of catastrophe are at an alarming rate of 3%. One might think that these tragedies make humans extinct. These estimates are not small, and possibly humans could invent or develop new technologies that increase the likelihood of existential risks. AI is the…

Ethical Use of AI gives a boost to students in narrowing topic and finding keywords : Today’s student have artificial intelligence or AI to perform various tasks that once took hours or even days to perform. AI can help in research, writing, and proofreading. Many of these tasks appear unethical to students who still prefer to do their work by themselves. However, if students provide a transparency statement in which they highlight how they perform the task using AI, they will not only improve their productivity, but even enhance the final outcome. In this article we will cover the four key points that you can include in your transparency statement if you are allowed to use AI. For the purpose of this article, consider a brief case study which I will use to show how you can develop an ethical statement. Assume that you are preparing an assignment for the course “organizational behavior” and you have studied topics like psychological contract, employee engagement, organizational culture, and organizational socialization. Additionally, assume that you work in police and recently your department has hired new recruits. Your department already has many officers. You are required to prepare a briefing to Police Minister and

The World Wide Web becomes the victim of a cross fire between ChatGPT and Google’s AI Overview In 2023, Google announced to introduce answer engines or more commonly known as Artificial Intelligence (AI) Overviews. This major feature in the browser powered by AI that offers a concise and complete responses directly on the search engine like an overview, reducing the need to click through websites. Google introduced AI Overview in response to ChatGPT. Traditionally, users need to type a query and Google mentioned relevant websites that are also optimized on its search engine. This requires users to check and skim various websites to find an answer. ChatGPT allows users to simply type a query and get a pinpoint answer. This reduced 7.91% global traffic from 2023-2024. When the AI Overview rolled out in May 2024 Google’s traffic increased by more than 49%. While this allowed Google to respond OpenAI, it also hit the internet’s core business model. One of the major impacts of AI Overview is that it reduced the websites’ traffic. Websites within an industry compete to appear on the first page and on the first position of the Google’s search engine. This provides advantage to gain users who

AI is penetrating but people often argue how. This article differentiates sense from nonsense. Artificial Intelligence (AI) likely impact various aspects of our lives and the world. Notably, the generative AI like ChatGPT has penetrated work and study. Can AI be so capable that it can make sense? To explore this, we need to understand how humans and AI think when a task is assigned to them. When you ask a human to do a task like bring a medicine from a pharmacy, they will not consider it as their mission or purpose. This means they won’t kill a pharmacist to get a medicine. However, the problem with AI is that it is given a fixed objective. The algorithm wants the scientist to clearly define the objective. For example, if you want AI to resolve acidification of the ocean it might do this with a catalytic reaction with extreme efficiency but it would consume so much oxygen that humans will die. Some might argue that we can specify to AI that be careful about oxygen in the environment and also other things like aquatic animals, seaweed, and so on. We have seen this in many movies like Clouding with a

Creativity was once a human trait, but it is now becoming common in machines. This article uncovers the issues in AI-generated artistic work. AI is not just restricted to answering questions, automating tasks, or generating codes, it is also doing creative work. This includes, but is not limited to, pictures, videos, artwork, or music. Is this artificial creativity really a creative work? In 1843, Lady Ada Lovelace – the World’s First Computer Programmer – argued that machines one day could think like a human if they intentionally programmed to do like humans. She further argues that a machine will be truly creative or intelligent if it is able to produce original ideas. These ideas of Lovelace also unfolded the definition of creativity, which must include two components: (1) a valuable, and (2) an original idea. In 2001, researchers created a LoveLace Test to separate creative ideas from non-creative ones. This test is especially designed for machines that claim to be creative like humans. The test identifies whether a machine can generate a result that cannot be explained by its source code. The Lovelace test is more like many of Einstein’s thought experiments rather than an objective scientific test. Suno AI

AI can help you in decision-making, but without any explanation of why it reaches such a decision reducing accountability and increasing self-fulfilling prophecy. Suppose you earn a fortune and decide to do a business startup. You are excited about the idea, but some statistics change your mind. You know that many startups fail because the idea is poor, partners are not committed to the business, or the idea is conceived poorly. You know that 90% startups fail within the first year. If your startup wouldn’t last for a year, you feel like investing resources in a venture would be a mistake. You live in the age of technology, and you heard that a company has released an AI model that can predict your likelihood of failure. The model is trained on datasets comprising hobbies of individuals, social media activities, online search histories, spending habits, and history of startups and failure. Based on this information, the AI can predict if a startup will fail within the first year of operations with 95% accuracy. The only problem with the model is that it does not give reasons behind its results. It simply predicts whether you will fail or won’t fail without saying