Elevate your enterprise data technology and strategy at Transform 2021.
As the common proverb goes, to err is human. One day, machines may offer workforce solutions that are free from human decision-making mistakes; however, those machines learn through algorithms and systems built by programmers, developers, product managers, and software teams with inherent biases (like all other humans). In other words, to err is also machine.
Artificial intelligence has the potential to improve our lives in countless ways. However, since algorithms often are created by a few people and distributed to many, its incumbent upon the creators to build them in a way that benefits populations and communities equitably. This is much easier said than done no programmer can be expected to hold the full knowledge and awareness necessary to build a bias-free AI model, and further, the data gathered can be biased as a result of the way they are collected and the cultural assumptions behind those empirical methods. Fortunately, when building continuously learning AI systems of the future, there are ways to reduce that bias within models and systems. The first step is about recognition.
Its important to recognize that bias exists in the real world, in all industries and among all humans. The question to ask is not how to make bias go away but how to detect and mitigate such bias. Understanding this helps teams take accountability to ensure that models, systems, and data are incorporating inputs from a diverse set of stakeholders and samples.
With countless ways for bias to seep into algorithms and their applications, the decisions that impact models should not be made in isolation. Purposefully cultivating a workgroup of individuals from diversified backgrounds and ideologies can help inform decisions and designs that foster optimal and equitable outcomes.
Recently, the University of Cambridge conducted an evaluation of over 400 models attempting to detect COVID-19 faster via chest X-rays. The analysis found many algorithms had both severe shortcomings and a high risk of bias. In one instance, a model trained on X-ray images of adult chests was tested on a data set of X-rays from pediatric patients with pneumonia. Although adults experience COVID-19 at a higher rate than children, the model positively identified cases disproportionally. Its likely because the model weighted rib sizes in its analysis, when in fact, the most important diagnostic approach is to examine the diseased area of the lung and rule out other issues like a collapsed lung.
One of the bigger problems in model development is that the datasets rarely are made available due to the sensitive nature of the data, so its often hard to determine how a model is making a decision. This illustrates the importance of transparency and explainability in both how a model is created and its intended use. Having key stakeholders (i.g., clinicians, actuaries, data engineers, data scientists, care managers, ethicists, and advocates) developing a model in a single data view can remove several human biases that have persisted due to the siloed nature of healthcare.
Its also worth noting that diversity extends much further than the people creating algorithms. Fair algorithms test for bias in the underlying data in their models. In the case of the COVID-19 X-ray models, this was the Achilles heel. The data sampled and collected to build models can underrepresent certain groups whose outcomes we want to predict. Efforts must be made to build more complete samples with contributions from underrepresented groups to better represent populations.
Without developing more robust data sets and processes around how data is recorded and ingested, algorithms may amplify psychological or statistical bias from how the data was collected. This will negatively impact each step of the model-building process, such as the training, evaluation, and generalization phases. However, by including more people from different walks of life, the AI models built will have a broader understanding of the world, which will go a long way toward reducing the inherent biases of a single individual or homogeneous group.
It may surprise some engineers and data scientists, but lines of code can create unfairness in many ways. For example, Twitter automatically crops uploaded images to improve user experience, but its engineers received feedback that the platform was incorrectly missing or misidentifying certain faces. After multiple attempts to improve the algorithm, the team ultimately realized that image trimming was a decision best made by people. Choosing the argmax (largest predicted probability) for finally outputting predictions amplifies disparate impact. An enormous number of test data sets, as well as scenario-based testing, are needed to neutralize these concerns.
There will always be gaps in AI models, yet its important to maintain accountability for them and correct them. And fortunately, when teams detect potential biases with a base model that is built and performs sufficiently, existing methods can be used to de-bias the data. Ideally, models shouldnt run without having a proper continuous feedback loop where predicted outputs are reused to train new versions. When working with diverse teams, data, and algorithms, building feedback-aware AI can reduce the innate gaps where bias can sneak in, yet without the diversity of inputs, AI models will just re-learn from its bias.
If individuals and teams are cognizant of the existence of bias, then they have the necessary tools at the data, algorithm, and human levels to build a more responsible AI. The best solution is to be aware that these biases exist and maintain safety nets to address them for each project and model deployment. What tools or approaches do you use to create algorithm fairness in your industry? And most importantly, how do you define the purpose behind each model?
Akshay Sharmaisexecutive vice president of artificial intelligence at digital health company Sharecare.
View post:
How to mitigate bias in AI - VentureBeat
- Chinese national arrested and charged with stealing AI trade secrets from Google - NPR - March 8th, 2024 [March 8th, 2024]
- President Biden Calls for Ban on AI Voice Impersonations During State of the Union - Variety - March 8th, 2024 [March 8th, 2024]
- Revolutionize Your Business with AWS Generative AI Competency Partners | Amazon Web Services - AWS Blog - March 8th, 2024 [March 8th, 2024]
- Broadcom Expects AI Demand to Help Offset Weakness Elsewhere - Yahoo Finance - March 8th, 2024 [March 8th, 2024]
- Micron Hits Record High With Analysts Calling It an 'Under-Appreciated AI Beneficiary' - Investopedia - March 8th, 2024 [March 8th, 2024]
- The Adams administration quietly hired its first AI czar. Who is he? - City & State New York - March 8th, 2024 [March 8th, 2024]
- AI likely to increase energy use and accelerate climate misinformation report - The Guardian - March 8th, 2024 [March 8th, 2024]
- This Artificial Intelligence (AI) Stock Could Double, and It Is Way Cheaper Than Nvidia - Yahoo Finance - March 8th, 2024 [March 8th, 2024]
- Fake images made to show Trump with Black supporters highlight concerns around AI and elections - The Associated Press - March 8th, 2024 [March 8th, 2024]
- Artificial intelligence and illusions of understanding in scientific research - Nature.com - March 8th, 2024 [March 8th, 2024]
- Analysis | House AI task force leaders take long view on regulating the tools - The Washington Post - March 8th, 2024 [March 8th, 2024]
- Don't Give Your Business Data to AI Companies - Dark Reading - March 8th, 2024 [March 8th, 2024]
- NIST, the lab at the center of Bidens AI safety push, is decaying - The Washington Post - March 8th, 2024 [March 8th, 2024]
- Essay | AI is Coming! Tips for Staying Calm and Carrying On - The Wall Street Journal - March 8th, 2024 [March 8th, 2024]
- AI can be easily used to make fake election photos - report - BBC.com - March 8th, 2024 [March 8th, 2024]
- 5 Artificial Intelligence (AI) Stocks That Could Make You a Millionaire - Yahoo Finance - March 8th, 2024 [March 8th, 2024]
- AI could be an extraordinary force for good. So why do our politicians still not have a plan? - The Guardian - March 8th, 2024 [March 8th, 2024]
- Mapping Disease Trajectories from Birth to Death with AI - Neuroscience News - March 8th, 2024 [March 8th, 2024]
- India plans 10,000-GPU sovereign AI supercomputer - The Register - March 8th, 2024 [March 8th, 2024]
- SAP enhances Datasphere and SAC for AI-driven transformation - CIO - March 8th, 2024 [March 8th, 2024]
- Jim Cramer names companies and sectors poised to rally on the AI wave - CNBC - March 8th, 2024 [March 8th, 2024]
- The job applicants shut out by AI: The interviewer sounded like Siri - The Guardian - March 8th, 2024 [March 8th, 2024]
- Microsoft confirms Surface and Windows AI event for March 21st - The Verge - March 8th, 2024 [March 8th, 2024]
- Adobes new Express app brings Firefly AI tools to iOS and Android - The Verge - March 8th, 2024 [March 8th, 2024]
- A Google AI Watched 30,000 Hours of Video GamesNow It Makes Its Own - Singularity Hub - March 8th, 2024 [March 8th, 2024]
- Palantir CEO Karp on TITAN, AI Warfare Technology - Bloomberg - March 8th, 2024 [March 8th, 2024]
- Elliptic Curve Murmurations Found With AI Take Flight - Quanta Magazine - March 8th, 2024 [March 8th, 2024]
- 5 AI Stocks to Buy in March 2024, According to Analysts - TipRanks.com - TipRanks - March 8th, 2024 [March 8th, 2024]
- Wix's new AI chatbot builds websites in seconds based on prompts - The Verge - March 8th, 2024 [March 8th, 2024]
- Amid record high energy demand, America is running out of electricity - The Washington Post - March 8th, 2024 [March 8th, 2024]
- AI Crypto Tokens in 5 Minutes: What to Know and Where to Start - Inc. - February 26th, 2024 [February 26th, 2024]
- 'The Worlds I See' by AI visionary Fei-Fei Li '99 selected as Princeton Pre-read - Princeton University - February 26th, 2024 [February 26th, 2024]
- AI is having a 1995 moment, analyst says - Business Insider - February 26th, 2024 [February 26th, 2024]
- Vatican research group's book outlines AI's 'brave new world' - National Catholic Reporter - February 26th, 2024 [February 26th, 2024]
- Honor's Magic 6 Pro launches internationally with AI-powered eye tracking on the way - The Verge - February 26th, 2024 [February 26th, 2024]
- Google explains Gemini's embarrassing AI pictures of diverse Nazis - The Verge - February 26th, 2024 [February 26th, 2024]
- Google cut a deal with Reddit for AI training data - The Verge - February 26th, 2024 [February 26th, 2024]
- What's the point of Elon Musk's AI company? - The Verge - February 26th, 2024 [February 26th, 2024]
- AI agents like Rabbit aim to book your vacation and order your Uber - NPR - February 26th, 2024 [February 26th, 2024]
- Announcing Microsofts open automation framework to red team generative AI Systems - Microsoft - February 26th, 2024 [February 26th, 2024]
- After Nvidia's latest blowout, here are 20 AI stocks expected to rise as much as 44% - Yahoo Finance - February 26th, 2024 [February 26th, 2024]
- 1 Exceptional AI Chip Stock Investors Need to Know About in 2024 - The Motley Fool - February 26th, 2024 [February 26th, 2024]
- Nvidia briefly hits $2 trillion valuation as AI frenzy grips Wall Street - Reuters - February 26th, 2024 [February 26th, 2024]
- AI Chatbots Can Guess Your Personal Information From What You ... - WIRED - October 18th, 2023 [October 18th, 2023]
- Harvard IT Launches Pilot of AI Sandbox to Enable Walled-Off Use ... - Harvard Crimson - October 18th, 2023 [October 18th, 2023]
- Advancing policing through AI: Insights from the global law ... - Police News - October 18th, 2023 [October 18th, 2023]
- Hochul announces new SUNY, IBM investments in AI - Olean Times Herald - October 18th, 2023 [October 18th, 2023]
- Nvidia's banking on TensorRT to expand its generative AI dominance - The Verge - October 18th, 2023 [October 18th, 2023]
- AI expands from MRFs to vehicles - Plastics Recycling Update - October 18th, 2023 [October 18th, 2023]
- AI Reads Ancient Scroll Charred by Mount Vesuvius in Tech First - Scientific American - October 18th, 2023 [October 18th, 2023]
- A DEEPer (squared) dive into AI Harvard Gazette - Harvard Gazette - October 18th, 2023 [October 18th, 2023]
- Florida bar weighs whether lawyers using AI need client consent - Reuters - October 18th, 2023 [October 18th, 2023]
- Cognizant and Vianai Systems Announce Strategic Partnership to ... - PR Newswire - October 18th, 2023 [October 18th, 2023]
- How AI could speed up scientific discoveries, from proteins to ... - NPR - October 18th, 2023 [October 18th, 2023]
- AI challenge to deliver better healthcare | Western Australian ... - Government of Western Australia - October 18th, 2023 [October 18th, 2023]
- Henry Kissinger: The Path to AI Arms Control - Foreign Affairs Magazine - October 18th, 2023 [October 18th, 2023]
- Stability AI releases StableStudio in latest push for open-source AI - The Verge - May 18th, 2023 [May 18th, 2023]
- Google CEO Sundar Pichai Predicts That This Profession Will Be ... - The Motley Fool - May 18th, 2023 [May 18th, 2023]
- Frances privacy watchdog eyes protection against data scraping in AI action plan - TechCrunch - May 18th, 2023 [May 18th, 2023]
- Investing in Hippocratic AI - Andreessen Horowitz - May 18th, 2023 [May 18th, 2023]
- As Alphabet flexes its AI prowess, there's a 'new elephant in the room' for Google - MarketWatch - May 18th, 2023 [May 18th, 2023]
- The Boring Future of Generative AI | WIRED - WIRED - May 18th, 2023 [May 18th, 2023]
- OpenAI readies new open-source AI model, The Information reports - Reuters.com - May 18th, 2023 [May 18th, 2023]
- What every CEO should know about generative AI - McKinsey - May 18th, 2023 [May 18th, 2023]
- AI creates images of the 'perfect' man and woman - Sky News - May 18th, 2023 [May 18th, 2023]
- Audit AI search tools now, before they skew research - Nature.com - May 18th, 2023 [May 18th, 2023]
- 3 Reasons C3.ai Stock Could Be Your Golden Ticket to the AI ... - InvestorPlace - May 18th, 2023 [May 18th, 2023]
- Zoom makes a big bet on AI with investment in Anthropic - VentureBeat - May 18th, 2023 [May 18th, 2023]
- AI voice phone scams are on the rise. Here's how to avoid them - USA TODAY - May 18th, 2023 [May 18th, 2023]
- Amazon is building an AI-powered conversational experience for ... - The Verge - May 18th, 2023 [May 18th, 2023]
- AI speculators need to 'differentiate between actual spending and investment' and hype: Strategist - Yahoo Finance - May 18th, 2023 [May 18th, 2023]
- AI Can Be Both Accurate and Transparent - HBR.org Daily - May 18th, 2023 [May 18th, 2023]
- You're Probably Underestimating AI Chatbots | WIRED - WIRED - May 18th, 2023 [May 18th, 2023]
- AI presents political peril for 2024 with threat to mislead voters - The Associated Press - May 18th, 2023 [May 18th, 2023]
- We need AI to help us face the challenges of the future - The Guardian - May 18th, 2023 [May 18th, 2023]
- End Of Googles Dominance? Stock Gets Rare Analyst Downgrade Over AI Fears - Forbes - May 18th, 2023 [May 18th, 2023]
- Watch 44 million atoms simulated using AI and a supercomputer - New Scientist - May 18th, 2023 [May 18th, 2023]
- AI Is The New Electricity: Bank Of America Picks 20 Stocks To Cash In On ChatGPT Hype - Forbes - March 2nd, 2023 [March 2nd, 2023]
- Tech Giants Are Barreling Headfirst Into an AI Arms Race - February 20th, 2023 [February 20th, 2023]
- Bing's AI Is Threatening Users. That's No Laughing Matter - TIME - February 20th, 2023 [February 20th, 2023]