The Sunday Brew #55
In this brew - Your Black Friday Offer | Prevalence Inflation & Algorithmic Bias | Sam Altman back to OpenAI, Binance CEO pleads guilty & steps down, and X sued Media Matters
Welcome to The Sunday Brew, weekly 1-2-3 newsletter by The Percolator. Every Sunday we drop in your inbox 1 story in a picture, 2 concepts, ideas or frameworks to expand your horizons and 3 news from the week, to keep you updated.
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TWO IDEAS, FRAMEWORKS OR CONCEPTS
This week we bring to you two concepts - Prevalence Inflation & Algorithmic Bias
Prevalence Inflation
Prevalence inflation, often referred to as "base rate fallacy" or "base rate neglect," is a cognitive bias where people tend to ignore the overall frequency or prevalence of a phenomenon when making judgments about a specific case.
In other words, individuals might focus too much on specific details or individual cases without considering the broader context. In statistical terms, prevalence inflation occurs when people overestimate the likelihood of an event without taking into account the actual base rate or prevalence of that event in the general population. This can lead to errors in judgment and decision-making, particularly when dealing with probabilities or statistical information.
For instance, if someone hears about a rare disease and knows someone who has it, they might overestimate the prevalence of the disease in the general population without considering how rare it actually is.
The Prevalence Inflation Hypothesis suggests a correlation with the rise in self-reported mental health conditions, gender dysphoria, and similar issues. This hypothesis posits that increased awareness, reduced stigma, or changes in diagnostic criteria may contribute to an apparent increase in the reported prevalence of mental disorders.
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Algorithmic Bias
Algorithmic bias has emerged as a notable concept in the field of artificial intelligence (AI). It pertains to the systematic and unjust discrimination observed in the outcomes produced by AI algorithms. Rather than being an inherent flaw in the algorithms themselves, algorithmic bias often originates from biases present in the training data used for the development and training of these algorithms.
This bias can manifest in different ways. Firstly, training data bias is a common issue, where the algorithm unintentionally perpetuates existing biases present in the data it was trained on. Additionally, biases can infiltrate the decision-making process through input data, with certain variables introducing discrimination, especially in relation to protected characteristics like race or gender. The outcomes of algorithms may also exhibit bias, favouring or disadvantaging specific demographic groups, influencing areas such as hiring processes, loan approvals, and criminal justice decisions.
A concerning aspect is the potential for a feedback loop, where biased outcomes generated by algorithms contribute to the reinforcement of existing societal inequalities. For example, a biased hiring algorithm may perpetuate gender or racial disparities in the workforce.
Effectively addressing algorithmic bias is an ongoing challenge, calling for collaboration among technologists, ethicists, policymakers, and other stakeholders to develop and implement effective solutions.
THREE NEWS FROM THE WEEK
Sam Altman returns to OpenAI as CEO
Sam Altman re-joined OpenAI as CEO just days after he was fired by the board.
In the days following Altman's firing, hundreds of OpenAI employees, including co-founder and board member Ilya Sutskever, signed a letter demanding that the remaining board members resign or they would leave. Microsoft CEO Satya Nadella also weighed in, saying that Altman and others from OpenAI would be joining Microsoft to start a "new advanced AI research team."
The pressure on the board mounted, and on 22nd Nov, they announced the return of Altman as CEO. The board also said that it would be reconstituted, with former Salesforce co-CEO Bret Taylor, former US treasury secretary Larry Summers, and current director Adam D'Angelo joining the board. Read More »»»
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Binance CEO pleads guilty & steps down
Changpeng Zhao, the founder and CEO of Binance, pleaded guilty to federal charges and stepped down from his position on November 21. This was part of a $4.3 billion settlement with the U.S. Department of Justice (DOJ) to resolve a years-long investigation into the world's largest cryptocurrency exchange.
The DOJ accused Binance of violating U.S. anti-money laundering (AML) laws by failing to implement adequate safeguards to prevent the exchange from being used for illicit transactions. Binance also admitted to failing to register as a money services business (MSB) with the Financial Crimes Enforcement Network (FinCEN), a violation of the Bank Secrecy Act (BSA).
Zhao personally pleaded guilty to one count of violating the BSA. As part of the settlement, he agreed to pay a $50 million fine and to step down as CEO of Binance for three years. Read More »»»
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X sued Media Matters for Defamation
X, formerly Twitter, sued Media Matters for defamation this week. The lawsuit stemmed from a report published by Media Matters that claimed that ads for major brands had appeared next to posts touting Adolf Hitler and the Nazi party on X.
X claimed that Media Matters defamed the platform by publishing a report that misrepresented the extent of extremist content on X, and alleged that Media Matters manipulated its findings by using accounts that exclusively followed major brands or users known to produce fringe content. Read More »»»
The Sunday Brew by The Percolator brings to you curated news on tech, business & entrepreneurship, from across the internet to give your week a perfect start.
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