RT Autism Capital 🧩 (@AutismCapital)🚨NEW: The founder of Wikipedia shares that Wikipedia has BLACKLISTED conservative news sources such as:Breitbart, Daily Caller, Epoch Times, FOX News, The Federalist, Blaze Media, The NY Post, Counter Punch, Daily Caller, and Daily Mail, Sputnik News, UNZ Review, News Nation, Newsmax, etc.While allowing liberal news sources such as: The NYT, WashPo, Axios, AP, Reuters, Snopes, NPR, CNN, The Nation, Mother Jones, Glad, TV Guide, Hollywood Reporter, HuffPo, Gizmodo/Engadget ...

There is a statutory framework and regulatory framework that has allowed this to happen. The concentration of these media outlets into these large corporations and the sort of compiling of all these affiliates into these single companies. Um so it's legal.I mean what nextar is attempting to do which we we can get into but the next business before the government is a a request for an accommodation. It's not just please apply the law but a request for you to change something for us. Um but with respect to lik ...

All right. First, I want to make sure. Can everyone hear me in the back.Yeah. Okay. So, let's get started.I want you to think back to the moment you woke up today. What was the first thing you did. Hit snooze on your alarm.Maybe you scrolled through social media. Decided whether to get up or stay in bed just a little longer. From the moment you opened your eyes, you were already making decisions, right.what to read, what to ignore, what to click. And by the time you'd picked your breakfast, you'd made dozen ...

There were ideas in history which changed everything. Fire, electricity, printing press, the internet and now we have artificial intelligence or AI. AI accelerates knowledge, enhances human potential and solves problems one has thought unsolvable.For example, AI can help us to defeat disease. AI now reflects, imitates, generates, calculates and increasingly decides. Decides for you, decides for me, decides for all of us.AI can now predict your decisions. is around education, healthcare, medicine, transporta ...

Bias in AI Performance - AI models exhibit bias based on gender, accent, and race, impacting their effectiveness for different users [2] - Speech recognition models show a significant disparity, with a 35% word error rate for African American speakers compared to 19% for white speakers [4] - Facial recognition models have a higher error rate of over 34% for darker-skinned women compared to less than 1% for light-skinned men [5] Real-World Consequences - Biased facial recognition models used by law enforcement can lead to disproportionate misidentification and incorrect arrests of black and brown individuals [7][8] - AI hiring tools can unintentionally downgrade resumes based on gendered terms, perpetuating historical gender biases [9][10] - In the medical field, AI models can underestimate the severity of illness in black patients due to biases in training data [15] Mitigation Strategies - Algorithmic auditing, involving rigorous testing on diverse datasets, is crucial for identifying and addressing bias in AI models [18] - Transparency is essential, requiring corporations to share the demographics of their training data and justify fairness metrics [19] - Creating diverse and inclusive datasets by including underrepresented voices in the building process is necessary to combat bias at the source [20]

Concerns Regarding Ed Martin's Investigation - The appointment of Ed Martin, given his past affiliations and lack of prosecutorial experience, raises concerns about bias in investigating Leticia James and Adam Schiff [3][4] - There are doubts about the legitimacy of any charges Martin might bring, with skepticism expressed about his team's competence and potential for harassment through investigations [5][6] Weaponization of Justice System - The discussion highlights concerns about the weaponization of public institutions against American citizens, potentially undermining the justice system and damaging individual lives [7][8][9] - The actions of the current administration could normalize the weaponization of the Justice Department, leading to future reciprocal actions and eroding trust in legitimate investigations [10][11][15] Mortgage Fraud Allegations - Mortgage fraud allegations against Leticia James and Adam Schiff are viewed with skepticism, with concerns that they are politically motivated and lack sufficient evidence of intent [18][19][20][21] Erosion of Norms and Rule of Law - The report emphasizes the erosion of democratic norms and the rule of law, likening the situation to that of a banana republic [13][16][17]

AI and Leadership - AI will change the way we work, demanding technically literate but deeply human leadership [2] - AI lacks consciousness and human emotion, making human interaction irreplaceable [3] - Inclusive leadership is a business-critical skill in the AI era [4] Inclusivity and Bias in AI - Products designed with a single perspective risk bias and exclusion at scale, impacting AI development [6] - A 2023 Stanford report indicated AI is predominantly built by males in limited geographical hubs [7] - The World Economic Forum's 2023 report showed that only 22% of AI professionals were women [7] - Biased AI decisions can damage people, trust, and brand reputation [9] - Inclusive leadership involves considering those not typically included, building solutions for non-average users [10] Practical Implementation of Inclusivity - When building or scaling a business, it is important to consider the needs of people with different nationalities and neurodiversity [12] - Smart businesses build for the future by considering inclusivity in design, such as office spaces [17] - Businesses that prioritize inclusivity are likely to be more profitable [18] - Leaders should question technology, invest in tools that augment human interaction, and consider who is excluded [21]

No, listen, you know, if you step back, what's happening here is, you know, I think President Trump is fundamentally reshaping the media landscape. And the way he's doing that is when he ran for election, he ran directly at these legacy broadcast media outlets, ABC, NBC, CBS for years, you know, government officials just allowed those entities with execs sitting in Hollywood and New York to dictate the political narrative. And he has fundamentally changed the game.I mean, you see that really having conseque ...

AI Bias & Fairness - AI systems mimic human intelligence, learning from data to make classifications and predictions [6][8] - Bias in AI arises from non-diverse or incomplete data, leading to unfair or discriminatory outcomes [3][4] - AI amplifies existing inequalities by reflecting and perpetuating biases present in the data it's trained on [18] - Assumptions about identity are not valid data, yet AI learns from these assumptions if they are included in the training data [3][4] Examples of AI Bias - Applicant tracking systems can penalize resumes based on gendered language due to biased training data [12][13] - Facial recognition systems misidentify African and Asian faces more frequently than white faces [14] - Voice assistants misunderstand non-white speakers nearly twice as often as white speakers, with error rates up to 35% [16] - Insurance algorithms may charge higher premiums to certain demographics based on biased risk models [16][17] Addressing AI Bias - It is crucial to question the data used to train AI, ensuring it represents the entire population [19] - Building diverse teams can help recognize and identify biases that others might miss [19] - Organizations should set ethical guidelines and audit AI systems for bias, making fairness a performance metric [19][20] - Transparency in AI systems is essential, with models providing citations and reasoning for their decisions [21]

Our next speaker is called Fedra. Fedra Romney. Now, she is a strategic systems architect.I know it's big. And she's also an author of the book The Mach Van Influent. That's two for two for Dutch.Come on, please clap for me right now. I'm doing very well. My Dutch is amazing.It means the power of influence in English. So that book is mostly written for women who are trying to navigate the male dominated hierarchies in the workspaces. And as we all know as humans wherever you are, we all have biases.We all b ...