Altszn.com
  • Home
  • Crypto
    • Altcoins
    • Bitcoin
    • Ethereum
    • Monero
    • XRP
    • Zcash
  • Web3
  • DeFi
  • NFTs
No Result
View All Result
Altszn.com
  • Home
  • Crypto
    • Altcoins
    • Bitcoin
    • Ethereum
    • Monero
    • XRP
    • Zcash
  • Web3
  • DeFi
  • NFTs
No Result
View All Result
Altszn.com
No Result
View All Result

Can blockchain help solve the Henrietta Lacks problem?

Altszn.com by Altszn.com
January 18, 2023
in Blockchain
0
Can blockchain help solve the Henrietta Lacks problem?
399
SHARES
2.3k
VIEWS
Share on FacebookShare on Twitter


Recidiviz has built a platform that connects the different databases, with the goal of identifying people who are already qualified for release but remain behind bars or on supervision. “Think of Recidiviz like Google Maps,” says Jacoby, who worked on Maps when she was at the tech giant. Google Maps takes in data from different sources – satellite images, street maps, local business data — and organizes it into one easy view. “Recidiviz does something similar with criminal justice data,” Jacoby explains, “making it easy to identify people eligible to come home or to move to less intensive levels of supervision.”

People like Jacoby’s uncle. His experience with incarceration is what inspired her passion for criminal justice reform in the first place.

The problems are vast

The U.S. has the highest incarceration rate in the world — 2 million people according to the watchdog group, Prison Policy Initiative — at a cost of $182 billion a year. The numbers could be a lot lower if not for an array of problems including inaccurate sentencing calculations, flawed algorithms and parole violations laws.

Sentencing miscalculations

To determine eligibility for release, the current system requires corrections officers to check 21 different requirements spread across five different databases for each of the 90 to 100 people under their supervision. These manual calculations are time prohibitive, says Jacoby, and fall victim to human error.

In addition, Recidiviz found that policies aimed at helping to reduce the prison population don’t always work correctly. A key example is time off for good behavior laws that allow inmates to earn one day off for every 30 days of good behavior. Some states’ data systems are built to calculate time off as one day per month of good behavior, rather than per day. Over the course of a decade-long sentence, Jacoby says these miscalculations can lead to a huge discrepancy in the calculated release data and the actual release date.

Algorithms

Commercial algorithm-based software systems for risk assessment continue to be widely used in the criminal justice system, even though a 2018 study published in Science Advances exposed their limitations. After the study went viral, it took three years for the Justice Department to issue a report on their own flawed algorithms used to reduce the federal prison population as part of the 2018 First Step Act. The program, it was determined, overestimated the risk of putting inmates of color into early-release programs.

Despite its name, Recidiviz does not build these types of algorithms for predicting recidivism, or whether someone will commit another crime after being released from prison. Rather, Jacoby says the company’s “descriptive analytics” approach is specifically intended to weed out incarceration inequalities and avoid algorithmic pitfalls.

Parole violation laws

Research shows that 350,000 people a year — about a quarter of the total prison population — are sent back not because they’ve committed another crime, but because they’ve broken a specific rule of their probation. “Things that wouldn’t send you or I to prison, but would send someone on parole,” such as crossing county lines or being in the presence of alcohol when they shouldn’t be, are inflating the prison population, says Jacoby.

It’s personal for the co-founder and CEO

“I grew up with an uncle who went into the prison system,” Jacoby says. At 19, he was sentenced to ten years in prison for a non-violent crime. A few months after being released from jail, he was sent back for a non-violent parole violation.

“For my family, the fact that one in four prison admissions are driven not by a crime but by someone who’s broken a rule on probation and parole was really profound because that happened to my uncle,” Jacoby says. The experience led her to begin studying criminal justice in high school, then college. She continued her dive into how the criminal justice system works as part of her Passion Project while at Google, a program that allows employees to spend 20 percent of their time on pro-bono work. Two colleagues whose family members had also been stuck in the system joined her.

As part of the project, Jacoby interviewed hundreds of people involved in the criminal justice system. “Those on the right, those on the left, agreed that bad data was slowing down reform,” she says. Their research brought them to North Dakota where they began to understand the root of the problem. The corrections department is making “huge, consequential decisions every day [without] … the data,” Jacoby says. In a new video by Recidiviz not yet released, Jacoby recounts her exchange with the state’s director of corrections who told her, “‘It’s not that we have the data and we just don’t know how to make it public; we don’t have the information you think we have.'”

A mock-up (with fake data) of the types of dashboards and insights that Recidiviz provides to state governments.

Recidiviz

As a software engineer, Jacoby says the comment made no sense to her — until she witnessed it first-hand. “We spent a lot of time driving around in cars with corrections directors and parole officers watching them use these incredibly taxing, frankly terrible, old data systems,” Jacoby says.

As they weeded through thousands of files — some computerized, some on paper — they unearthed the consequences of bad data: Hundreds of people in prison well past their release date and thousands more whose release from parole was delayed because of minor paperwork issues. They found individuals stuck in parole because they hadn’t checked one last item off their eligibility list — like simply failing to provide their parole officer with a paystub. And, even when parolees advocated for themselves, the archaic system made it difficult for their parole officers to confirm their eligibility, so they remained in the system. Jacoby and her team also unpacked specific policies that drive racial disparities — such as fines and fees.

The Solution

It’s more than a trivial technical challenge to bring the incomplete, fragmented data onto a 21st century data platform. It takes months for Recidiviz to sift through a state’s information systems to connect databases “with the goal of tracking a person all the way through their journey and find out what’s working for 18- to 25-year-old men, what’s working for new mothers,” explains Jacoby in the video.

Ojmarrh Mitchell, an associate professor in the School of Criminology and Criminal Justice at Arizona State University, who is not involved with the company, says what Recidiviz is doing is “remarkable.” His perspective goes beyond academic analysis. In his pre-academic years, Mitchell was a probation officer, working within the framework of the “well known, but invisible” information sharing issues that plague criminal justice departments. The flexibility of Recidiviz’s approach is what makes it especially innovative, he says. “They identify the specific gaps in each jurisdiction and tailor a solution for that jurisdiction.”

On the downside, the process used by Recidiviz is “a bit opaque,” Mitchell says, with few details available on how Recidiviz designs its tools and tracks outcomes. By sharing more information about how its actions lead to progress in a given jurisdiction, Recidiviz could help reformers in other places figure out which programs have the best potential to work well.

The eleven states in which Recidiviz is working include California, Colorado, Maine, Michigan, Missouri, Pennsylvania and Tennessee. And a pilot program launched last year in Idaho, if scaled nationally, with could reduce the number of people in the criminal justice system by a quarter of a million people, Jacoby says. As part of the pilot, rather than relying on manual calculations, Recidiviz is equipping leaders and the probation officers with actionable information with a few clicks of an app that Recidiviz built.

Mitchell is disappointed that there’s even the need for Recidiviz. “This is a problem that government agencies have a responsibility to address,” he says. “But they haven’t.” For one company to come along and fill such a large gap is “remarkable.”



Read More: news.google.com

Tags: BlockchainHenriettalacksproblemsolveTech
ADVERTISEMENT

Recent

Danger signs for Bitcoin as retail abandons it to institutions: Sky Wee

Danger signs for Bitcoin as retail abandons it to institutions: Sky Wee

May 14, 2025
Crypto VC deals drop in Q1, but funding more than doubles: PitchBook

Crypto VC deals drop in Q1, but funding more than doubles: PitchBook

May 14, 2025
Ether Nears $2.7K, Dogecoin Zooms 9% to Keep Cheery Mood Ongoing

Ether Nears $2.7K, Dogecoin Zooms 9% to Keep Cheery Mood Ongoing

May 14, 2025

Categories

  • Bitcoin (4,880)
  • Blockchain (11,447)
  • Crypto (9,390)
  • Dark Web (551)
  • DeFi (8,414)
  • Ethereum (4,926)
  • Metaverse (7,576)
  • Monero (290)
  • NFT (1,504)
  • Solana (5,054)
  • Web3 (20,763)
  • Zcash (509)

Category

Select Category

    Advertise

    Advertise your site, company or product to millions of web3, NFT and cryptocurrency enthusiasts. Learn more

    Useful Links

    Advertise
    DMCA
    Contact Us
    Privacy Policy
    Shipping & Returns
    Terms of Use

    Resources

    Exchanges
    Changelly
    Web3 Jobs

    Recent News

    Danger signs for Bitcoin as retail abandons it to institutions: Sky Wee

    Danger signs for Bitcoin as retail abandons it to institutions: Sky Wee

    May 14, 2025
    Crypto VC deals drop in Q1, but funding more than doubles: PitchBook

    Crypto VC deals drop in Q1, but funding more than doubles: PitchBook

    May 14, 2025

    © 2022 Altszn.com. All Rights Reserved.

    No Result
    View All Result
    • Home
      • Home – Layout 1
      • Home – Layout 2
      • Home – Layout 3

    © Altszn.com. All Rights Reserved.

    • bitcoinBitcoin (BTC) $ 103,493.00
    • ethereumEthereum (ETH) $ 2,594.86
    • tetherTether (USDT) $ 1.00
    • xrpXRP (XRP) $ 2.55
    • bnbBNB (BNB) $ 650.96
    • solanaSolana (SOL) $ 176.08
    • usd-coinUSDC (USDC) $ 0.999907
    • dogecoinDogecoin (DOGE) $ 0.232138
    • cardanoCardano (ADA) $ 0.796234
    • tronTRON (TRX) $ 0.276675
    • staked-etherLido Staked Ether (STETH) $ 2,594.28
    • wrapped-bitcoinWrapped Bitcoin (WBTC) $ 103,526.00
    • suiSui (SUI) $ 3.91
    • chainlinkChainlink (LINK) $ 16.90
    • wrapped-stethWrapped stETH (WSTETH) $ 3,128.88
    • avalanche-2Avalanche (AVAX) $ 24.86
    • stellarStellar (XLM) $ 0.303278
    • shiba-inuShiba Inu (SHIB) $ 0.000016
    • hedera-hashgraphHedera (HBAR) $ 0.206137
    • hyperliquidHyperliquid (HYPE) $ 24.93
    • leo-tokenLEO Token (LEO) $ 8.89
    • the-open-networkToncoin (TON) $ 3.24
    • bitcoin-cashBitcoin Cash (BCH) $ 402.00
    • litecoinLitecoin (LTC) $ 101.28
    • polkadotPolkadot (DOT) $ 4.98
    • usdsUSDS (USDS) $ 0.999802
    • wethWETH (WETH) $ 2,594.34
    • pi-networkPi Network (PI) $ 0.913169
    • moneroMonero (XMR) $ 337.30
    • wrapped-eethWrapped eETH (WEETH) $ 2,775.74
    • pepePepe (PEPE) $ 0.000014
    • bitget-tokenBitget Token (BGB) $ 4.75
    • binance-bridged-usdt-bnb-smart-chainBinance Bridged USDT (BNB Smart Chain) (BSC-USD) $ 1.00
    • ethena-usdeEthena USDe (USDE) $ 1.00
    • coinbase-wrapped-btcCoinbase Wrapped BTC (CBBTC) $ 103,548.00
    • whitebitWhiteBIT Coin (WBT) $ 30.31
    • bittensorBittensor (TAO) $ 454.25
    • uniswapUniswap (UNI) $ 6.59
    • nearNEAR Protocol (NEAR) $ 3.04
    • daiDai (DAI) $ 1.00
    • aptosAptos (APT) $ 5.72
    • aaveAave (AAVE) $ 228.60
    • okbOKB (OKB) $ 54.16
    • ondo-financeOndo (ONDO) $ 1.01
    • jito-staked-solJito Staked SOL (JITOSOL) $ 211.37
    • kaspaKaspa (KAS) $ 0.119463
    • ethereum-classicEthereum Classic (ETC) $ 19.78
    • internet-computerInternet Computer (ICP) $ 5.63
    • crypto-com-chainCronos (CRO) $ 0.101695
    • tokenize-xchangeTokenize Xchange (TKX) $ 36.18
    • bitcoinBitcoin (BTC) $ 103,493.00
    • ethereumEthereum (ETH) $ 2,594.86
    • tetherTether (USDT) $ 1.00
    • xrpXRP (XRP) $ 2.55
    • bnbBNB (BNB) $ 650.96
    • solanaSolana (SOL) $ 176.08
    • usd-coinUSDC (USDC) $ 0.999907
    • dogecoinDogecoin (DOGE) $ 0.232138
    • cardanoCardano (ADA) $ 0.796234
    • tronTRON (TRX) $ 0.276675
    • staked-etherLido Staked Ether (STETH) $ 2,594.28
    • wrapped-bitcoinWrapped Bitcoin (WBTC) $ 103,526.00
    • suiSui (SUI) $ 3.91
    • chainlinkChainlink (LINK) $ 16.90
    • wrapped-stethWrapped stETH (WSTETH) $ 3,128.88
    • avalanche-2Avalanche (AVAX) $ 24.86
    • stellarStellar (XLM) $ 0.303278
    • shiba-inuShiba Inu (SHIB) $ 0.000016
    • hedera-hashgraphHedera (HBAR) $ 0.206137
    • hyperliquidHyperliquid (HYPE) $ 24.93
    • leo-tokenLEO Token (LEO) $ 8.89
    • the-open-networkToncoin (TON) $ 3.24
    • bitcoin-cashBitcoin Cash (BCH) $ 402.00
    • litecoinLitecoin (LTC) $ 101.28
    • polkadotPolkadot (DOT) $ 4.98
    • usdsUSDS (USDS) $ 0.999802
    • wethWETH (WETH) $ 2,594.34
    • pi-networkPi Network (PI) $ 0.913169
    • moneroMonero (XMR) $ 337.30
    • wrapped-eethWrapped eETH (WEETH) $ 2,775.74
    • pepePepe (PEPE) $ 0.000014
    • bitget-tokenBitget Token (BGB) $ 4.75
    • binance-bridged-usdt-bnb-smart-chainBinance Bridged USDT (BNB Smart Chain) (BSC-USD) $ 1.00
    • ethena-usdeEthena USDe (USDE) $ 1.00
    • coinbase-wrapped-btcCoinbase Wrapped BTC (CBBTC) $ 103,548.00
    • whitebitWhiteBIT Coin (WBT) $ 30.31
    • bittensorBittensor (TAO) $ 454.25
    • uniswapUniswap (UNI) $ 6.59
    • nearNEAR Protocol (NEAR) $ 3.04
    • daiDai (DAI) $ 1.00
    • aptosAptos (APT) $ 5.72
    • aaveAave (AAVE) $ 228.60
    • okbOKB (OKB) $ 54.16
    • ondo-financeOndo (ONDO) $ 1.01
    • jito-staked-solJito Staked SOL (JITOSOL) $ 211.37
    • kaspaKaspa (KAS) $ 0.119463
    • ethereum-classicEthereum Classic (ETC) $ 19.78
    • internet-computerInternet Computer (ICP) $ 5.63
    • crypto-com-chainCronos (CRO) $ 0.101695
    • tokenize-xchangeTokenize Xchange (TKX) $ 36.18