O rompimento do mundo dos humanos

 

By

Eliane Brum

El País

 

No princípio era o verbo. A frase que abre o primeiro capítulo do Evangelho de João e remete à criação do mundo, assim como também faz o Gênesis, é a mais famosa da Bíblia. A ideia de que o mundo é criado pela palavra, porém, é tão estruturante que está presente em outras religiões, para muito além das fundadas no cristianismo. Como humanos, a linguagem é o mundo que habitamos. Basta tentar imaginar um mundo em que não podemos usar palavras para dizer de nós e dos outros para compreender o que isso significa. Ou um mundo em que aquilo que você diz não é entendido pelo outro, e o que o outro diz não é entendido por você, para alcançar o que é ser reduzido a sons porque as palavras perderam seu significado e, portanto, se tornaram fantasmagorias. Quando uso a palavra “dizer” não significa apenas falar, porque a gente se diz com palavras, de várias maneiras para além da fala. Mais ainda do que o mundo que habitamos, a palavra é o que nos tece. Aquilo que chamamos mundo é uma trama de palavras.

O que acontece então quando a palavra é destruída e, com ela, a linguagem?

Essa é a experiência do bolsonarismo, nome dado no Brasil a um fenômeno que se dissemina no planeta, ganhando em outros países nomes de outros déspotas. Os personagens que emprestam nomes locais ao fenômeno são importantes e, em cada país, há particularidades. Mas o fenômeno precede aqueles que o encarnam e, infelizmente, irá além deles. É neste contexto que busco interpretar o Nobel da Paz dado a dois jornalistas que lutam pela busca da verdade contra ditadores eleitos que têm na destruição da palavra seu principal meio para alcançar e se perpetuar no poder.

A filipina Maria Ressa está proibida de sair de seu país, já foi presa duas vezes e pagou fiança outras sete por combater com jornalismo o governo de Rodrigo Duterte. Ela é editora do site de reportagem investigativa Rappler. O russo Dmitri Muratov dirige o jornal Novaia Gazeta, que ousa confrontar com fatos o regime de Vladimir Putin. Desde 2001, seis repórteres do jornal foram assassinados. A escolha de dar o Nobel a esses dois jornalistas que são símbolos da resistência contra a opressão em seus países é uma declaração da importância da imprensa para a democracia. O Nobel, prêmio que destaca aqueles que colaboraram para o bem comum, representa o conceito de humanidade consolidado ao longo do século 20. Como bem comum e democracia se tornaram uma espécie de irmãos siameses no mundo do pós-guerra, um prêmio a jornalistas no Nobel da Paz faz todo sentido. Mas em que momento chega esse prêmio à imprensa, na conturbada terceira década do século 21?

A justiça da premiação a esses dois jornalistas é inegável. A escolha de valorizar a imprensa como pilar da democracia e, assim, valorizar a busca das verdades, assim mesmo no plural, e a importância dos fatos, num momento em que um e outro estão corroídos, também. A questão é: quem escuta?

Se jornalistas são atacados e desqualificados, se outros são presos e outros ainda executados é porque a imprensa ainda tem impacto sobre a sociedade. Suspeito, porém, que estamos chegando, pelo menos no Brasil, a um momento ainda mais grave. Para uma parte da população, a imprensa já não importa em nada. Todas as iniciativas de expor a mentira das chamadas fake news, entre elas as agências de checagem, são muito importantes. Mas são muito importantes apenas —ou pelo menos principalmente— para aqueles que respeitam os fatos e já sabem que aquelas notícias são falsas. Para todos os outros, já houve uma decisão prévia de que tudo o que a imprensa publica é falso. Esta é a razão pela qual em golpes como o de Jair Bolsonaro não é necessário censura, como aconteceu em ditaduras passadas, já que para essa parcela da população nada que seja estampado nas manchetes dos jornais vai colar.

Isso não significa que os jornalistas deixarão de correr riscos. Como o governo Bolsonaro mostrou, os ataques são necessários para manter o apartheid político ativo. Se forem contra jornalistas mulheres, melhor ainda, na medida em que a misoginia e o machismo rendem votos para Bolsonaro. É importante que a base de seguidores seja mantida em estado de ódio constante e seja lembrada, também de forma constante, que a imprensa “só diz mentiras”. A estratégia torna mais fácil fabricar “fatos alternativos” como se verdade fossem. “Fatos alternativos” são impossibilidades lógicas. São também mentiras facilmente desmontáveis, como as agências de checagem demonstram toda vez. Mas, se uma parte da população não lê nem vê nem escuta, de que adianta?

O que está em jogo é algo mais profundo: uma mudança na forma de apreensão da realidade, que confronta os pilares que forjaram a imprensa e o funcionamento da sociedade moderna. Por uma série de razões, o verbo que progressivamente passou a mediar uma parcela significativa das pessoas na sua relação com a realidade é “acreditar”. Não mais os verbos iluministas do duvidar, investigar, testar, confrontar, comparar etc. Mas acreditar. É uma mediação religiosa da realidade, determinada pela fé. A crença se antecipa aos fatos, e assim os fatos já não importam. É como se as pessoas passassem a ler a realidade da mesma forma que leem a Bíblia. Esta é a razão que determina a crise da imprensa, da ciência e de outros fundamentos que constituíram a modernidade, baseados na investigação e no questionamento constante, para os quais a dúvida é que move o processo de apreensão da realidade e de construção do conhecimento sobre o mundo.

É claro que essa mudança tem relação com o crescimento de um determinado tipo de religião, no Brasil marcadamente a expansão do neopentecostalismo de mercado, através de denominações religiosas produzidas por essa fase ainda mais predatória do capitalismo. Na minha interpretação, porém, a mediação da realidade pela fé é (não só, mas) principalmente sintoma da transfiguração do planeta pela crise climática. Ainda que a maioria das pessoas não seja capaz de nomear os impactos dessa monumental mudança em suas vidas, todos estão sentindo que o mundo que conhecem se desfaz debaixo dos pés. Mesmo para aqueles que a vida cotidiana sempre foi muito dura, a dureza desconhecida é ainda mais brutal do que a conhecida. No desamparo, em que também as instituições se desfazem, resta crer. E resta crer mesmo para aqueles não religiosos, no sentido estrito. E resta crer não apenas numa religião, mas em uma realidade que, se não é real no sentido de corresponder aos fatos, se torna real para quem nela acredita. Nesta proposição, a mediação da realidade pela crença seria uma adaptação à emergência climática que, em vez de enfrentá-la, a agrava.

Como já escrevi mais de uma vez, os ditadores eleitos que alcançaram o poder pelo voto a partir da segunda década do século são vendedores de passados que nunca existiram porque não têm futuro para oferecer, já que as forças que representam são as principais responsáveis pela alteração do clima e da morfologia do planeta. No caso de Jair Bolsonaro, principalmente os setores do agronegócio predatório e da mineração. A aliança alcançada no bolsonarismo entre agronegócio, mineração, corporações transnacionais de agrotóxicos e produtos ultraprocessados e grandes pastores do neopentecostalismo de mercado não é um acaso. Em comum, essas forças buscam seguir avançando sobre a natureza e lucrando num momento em que são confrontadas pela corrosão do planeta. No Brasil, especialmente pela destruição da Amazônia, que pode chegar ao ponto de não retorno nos próximos anos. Mas também a destruição persistente de outros biomas e de seus povos, como o Cerrado e o Pantanal.

Só a mediação da realidade pela crença pode garantir a continuidade da exploração e do lucro pelas grandes corporações capitalistas num momento em que o planeta superaquece devido a suas ações. É por isso que parte dos executivos de corporações transnacionais toleram a companhia pouco refinada dos pastores de mercado e principalmente de uma criatura tosca como Jair Messias Bolsonaro, que tem levado a crença como ativo político ao paroxismo. A palavra “seguidores”, tomada emprestada das seitas e religiões pelas redes sociais, tornou-se sinalizadora de um fenômeno na política em que mesmo os ateus se comportam como crentes. Pela tomada da política pela mediação religiosa, ironicamente a mais famosa frase bíblica foi traída. No princípio era o verbo. Mas então o verbo passa a ser sistematicamente destruído como projeto de poder.

Nessa fase, portanto, ainda é necessário bater na imprensa e trabalhar para a desqualificação de jornalistas. Talvez numa segunda fase já não será mais preciso, na medida em que a imprensa poderá seguir importante, mas apenas para uma bolha, e com dificuldades cada vez maiores para penetrar em universos além dela. Este é hoje o grande desafio do jornalismo e do mundo que produziu a imprensa como a conhecemos.

As próximas eleições quase certamente ampliarão o fosso no mundo dos humanos. A ótima reportagem sobre o avanço do Telegram entre a extrema direita global, publicada no jornal O Globo, aponta a estratégia em acelerada execução. Sem representação legal no país nem moderação de conteúdo, o Telegram não respondeu às tentativas de contato da Justiça brasileira. Com grupos para até 200 mil pessoas e canais com capacidade ilimitada de inscritos, o Telegram é o mundo perfeito para a propaganda em massa sem a necessidade de atender à legislação dos países. Subverte, em nome da “liberdade de expressão”, o próprio conceito de liberdade de expressão, em que limites precisam ser respeitados para que o crime não se imponha. No Telegram, por exemplo, circulam livremente vídeos com pornografia infantil, assim como armas são comercializadas sem nenhuma normatização e fiscalização.

A partir das denúncias do uso ilegal do WhatsApp na campanha de Bolsonaro, em 2018, o aplicativo de mensagens de Mark Zuckerberg tomou algumas medidas para impedir ou pelo menos controlar minimamente a disseminação de fake news para uso eleitoral. Como alternativa para a eleição de 2022, Bolsonaro passou a apostar então no Telegram: na semana passada, seu canal no aplicativo bateu a marca de 1 milhão de seguidores. Fundado em 2013 na Rússia pelos irmão Nikolai e Pavel Durov, com sede em Dubai, nos últimos anos o Telegram teria mudado de jurisdição várias vezes para escapar de qualquer regulação. Os auxiliares de Bolsonaro hoje trabalham arduamente para construir na plataforma uma base de crentes políticos capazes de levá-lo à reeleição. Donald Trump, por sua vez, depois da criminosa invasão do Capitólio, foi banido das redes sociais Twitter e Facebook, por meio das quais propagava suas mentiras e insuflava seus seguidores. Seu ex-conselheiro, Jason Miller, lançou então neste ano uma nova rede social, a Gettr. Em setembro, Miller foi recebido por Bolsonaro no Palácio do Alvorada.

É na internet que está sendo forjada uma realidade sem lastro nos fatos. Neste ato em processo, os pilares do mundo que conhecíamos são corroídos. Entre eles, a imprensa, a ciência e a democracia. É importante fazer a ressalva de que obviamente não vivíamos num mundo maravilhoso que foi corrompido por homens do mal. A democracia nunca chegou para todos. É notório que grande parte da população brasileira viveu na arbitrariedade das forças policiais mesmo após a redemocratização do país e também sem acesso a direitos básicos. O mesmo vale para outros países, inclusive para as parcelas pobres de países considerados ricos, como o brutalmente desigual Estados Unidos.

No Brasil, a imprensa —branca, majoritariamente liberal, liderada preferencialmente por homens e com posições ocupadas pelos filhos da classe média que puderam chegar à universidade e, mais recentemente, aos MBAs nos Estados Unidos e na Europa— nunca representou a diversidade da sociedade brasileira, deixando largas camadas fora dela e dando diferentes valores à vida humana. Basta ver o espaço dado à morte dos ricos (e brancos) e à dos pobres (e pretos), à vida dos ricos (e brancos) e à dos pobres (e pretos). Só recentemente, por pressão externa, a imprensa tem aberto espaço aos negros, maioria da população, e começado a se abrir para a diversidade de gênero. Vale dizer ainda que, disposta a defender seus lucros e interesses, no Brasil as principais famílias que dominam a mídia impediram o avanço do debate da regulamentação da imprensa como se fosse um atentado à liberdade de expressão e, assim, uma grande parte das concessões públicas de TV é usada (e abusada) pela mais nefasta doutrinação religiosa disseminadora de teorias conspiratórias e anticientíficas.

A ciência tampouco escapa de um olhar crítico. É responsável direta pela emergência climática, processo de alteração do clima e da morfologia do planeta iniciado na Revolução Industrial e acelerado no século 20. Sem contar que fez muitas promessas que não foi capaz de cumprir —e ainda faz. Em países como o Brasil, em que a educação é uma tragédia jamais enfrentada com o investimento necessário, a maior parte da população não é capaz de compreender a ciência que impacta a sua vida e jamais houve preocupação suficiente de seus agentes para mudar esse estado geral de ignorância por falta de acesso à informação científica inteligível.

Isso não significa, porém, que a democracia, a imprensa e a ciência sejam menos do que essenciais para a criação de um futuro em que possamos viver. Com todas as suas falhas, omissões e exclusões, esses três pilares conectados são parte do melhor que a humanidade produziu. É (também) com muita ciência, obrigatoriamente contando com o conhecimento ancestral de povos-natureza, como os indígenas, que temos alguma chance de enfrentar o superaquecimento global e a monumental perda de biodiversidade. É também dentro da própria imprensa que têm surgido as melhores críticas à imprensa. A melhor forma de enfrentar os problemas da imprensa é com jornalismo da melhor qualidade, feito com rigor e honestidade. Ampliar a democracia é também o melhor caminho disponível para enfrentar sua crise. E, num momento de ecocídios em curso, é preciso ampliá-la também para outras espécies.

Durante séculos, em diferentes sociedades e línguas, é importante lembrar, a linguagem serviu —e ainda serve— para manter privilégios de grupos de poder e deixar todos os outros de fora. Quem entende linguagem de advogados, juízes e promotores, linguagem de médicos, linguagem de burocratas, linguagem de cientistas? A maior parte da população foi submetida à violência de propositalmente ser impedida de compreender a linguagem daqueles que determinam seus destinos. E então surgem criaturas como Jair Bolsonaro e outros que falam na língua que são capazes de entender. E mentem na língua que entendem. E dizem que é ótimo não entender nada sobre quase tudo. Parte da população decide, como reação, dar a pior resposta à sua exclusão fazendo e exercendo a exaltação da ignorância. Criam sua própria bolha de linguagem e passam a excluir todos os outros. É estúpido, mas é uma reação. Afinal, por séculos poucos se importaram que grandes parcelas das populações do planeta ficassem de fora da linguagem em que suas vidas eram decididas.

Ressalvas feitas, o momento é brutal. É na brutalidade do que vivemos que o Nobel da Paz dado a dois jornalistas pode ser interpretado como o grito desesperado de quem assiste a pilares como a imprensa desabarem. Não porque a imprensa deixará de existir, mas porque poderá ter impacto apenas sobre uma parte da população —o que é diferente do passado recente, em que também era feita e controlada por uma minoria, mas tinha impacto sobre o conjunto da sociedade. Trata-se em parte de uma reorganização dos espaços de poder, mas feita da pior maneira possível e, em grande medida, falsa, já que corrói a possibilidade de qualquer transformação real. Ao final, os principais beneficiados são minoritários e os mesmos de sempre, razão pela qual Bolsonaro continua no poder apesar de todos os seus crimes. Em um mundo em transtorno climático, as grandes corporações decidiram sacrificar parte de seus aliados históricos para manter um sistema que colocou a espécie diante da possibilidade de extinção.

Esse é o abismo do qual nos aproximamos. Estamos à beira de algo com a magnitude do rompimento da linguagem que une os humanos, para além das diferenças de língua: uma parcela da população global aderindo a uma realidade falsificada, mas que, pela adesão, passa a se tornar real. Tudo indica que as eleições de 2022, no Brasil, serão o laboratório de ensaio dessa nova fase da crise da palavra, para muito além do que se entende por polarização. Ao romper a linguagem com a qual é possível se encontrar, aquela que compartilha de uma base de significados de consenso baseado em evidências, sejam elas objetivas ou subjetivas, estamos diante de um fenômeno inédito. Num planeta em colapso climático, em que mais do que nunca é necessária uma linguagem comum para determinar o comum pelo qual lutar, a humanidade parece se dividir em duas gigantescas bolhas impermeáveis uma a outra.

Lutar pelo futuro é lutar no presente para que as palavras voltem a encarnar, permitindo uma linguagem comum. Não como antes, mas uma em que realmente caibam todas as gentes e suas diferenças, tornando o debate das ideias possível para a criação de conhecimento e de ação baseada em conhecimento. O que tínhamos não era justo e nos trouxe até esse momento limite. Para seguirmos existindo, teremos que ser melhores do que fomos e criar uma sociedade capaz de viver em paz com todas as forças de vida do planeta. Se o princípio é o verbo, o fim pode ser o silenciamento. Mesmo que ele seja cheio de gritos entre aqueles que já não têm linguagem comum para compreender uns aos outros.

 

Billionaires in Space

 

By A.M. Gittlitz 

“Welcome to the dawn of a new space age,” said billionaire Richard Branson after the successful launch and landing of his spaceship the VSS Unity. The test flight for Branson’s space tourism venture, Virgin Galactic, was indeed a fitting inauguration of this new, neoliberal space age, which substitutes corporate noblesse oblige for the cosmic vision of collective progress that space travel once represented.

With this test run completed, more people may now be able to experience suborbital spaceflights. Fellow billionaires Elon Musk and Jeff Bezos have lined up for their own 11 minutes of heaven, the result of decades of work, billions in investment, and endless campaigns portraying their respective vanity NASA clones, SpaceX and Blue Origin, as laying the groundwork for humanity’s salvation. Their sojourns, however, bear more resemblance to extreme tourism, like skydiving or zero-gravity flights, than to the lunar commuter jets of 2001: A Space Odyssey.

Despite the technical innovation of these spaceplanes, the voyages themselves fail to surpass even that of the earliest cosmonaut, Yuri Gagarin, a former steelworker who traveled 203 miles above the surface of the planet to complete a full orbit of it in 1961. Sixty years later, Branson’s hour-long flight reached a peak altitude of 53 miles, yielding a brief weightless glimpse of Earth’s curvature. But more galling than the footage of his barrel rolls was his dedication of the flight to a new generation of aspiring astronauts, now potential Virgin Galactic customers. Gagarin, on the other hand, returned stunned by the beauty of our fragile planet, with a determination to “preserve and increase this beauty, not destroy it!”

These luxury flights also represent a reversal of American astronaut Neil Armstrong’s declaration that space travel was in the interest of all mankind. Armstrong’s words not only articulated the sentiment of many of the 650 million people who watched his first steps on the moon—the single most unifying event in human history—but of international law. The 1967 United Nations–ratified Outer Space Treaty legislated that “exploration and use of outer space shall be carried out for the benefit and in the interests of all countries and shall be the province of all mankind.” That the space race was a Cold War proxy did not deflate the hope that the US and USSR flags carried to the moon represented something beyond endless war and greed.

Sadly, the UN treaty exploded not long after takeoff. Instead of a cosmic commons, space is treated as a frontier of private resource extraction and militarization. Alongside SpaceX and Blue Origin, some of the world’s largest defense contractors like Boeing and Lockheed Martin have won billions in government contracts to pioneer space technologies. Billions more have been allocated to the Space Force, the newest branch of the military, created by President Trump and backed by President Biden. Its mission is to realize an outlandish extension of American manifest destiny by securing military communications and creating a “space fence” for orbital surveillance.

Just as the Space Force adopted a Star Trek aesthetic to present American expansion in the image of human progress, the billionaires’ spaceships allude to golden-age science fiction to cover their role in building a dystopian future. Their most fantastical visions—Bezos’s Elysium-style floating colonies, where every day feels like summer in Maui, and Musk’s blueprints for a Martian Galt’s Gulch staffed by debt peons—are a long way from plausible. But their entrenchment in the growing markets of satellite Internet, space tourism, and militarization bespeaks a deepening influence on global geopolitics.

Yet even billionaires are forced to use the language of collectivity that space travel, both scientific and science-fictional, has always carried with it. Bezos’s Blue Origin claims a larger vision of “millions of people…living and working in space to benefit Earth.” Branson says Virgin Galactic, whose flights currently start at $200,000 a ticket, will “open space to everybody.” While SpaceX promotes Mars colonization as having the potential to make humanity a “multiplanetary species,” Musk admitted in an interview with Joe Rogan that “if this species is going to survive, we kind of have to escape.”

This nihilistic sentiment inadvertently reveals the anxieties of the one percent. We are already in an era of civilizational catastrophe fueled by political, economic, and environmental instability. Elite schemes of private islands and apocalypse bunkers no longer seem adequate to repel the inevitable billions of climate and war refugees, unemployed and precarious workers, and everyone else immiserated by the barbarity of the current order. There is only one way left to run: up.

Ironically, there are few better examples of how human cooperation can overcome such seemingly impossible challenges than the original space race. At its peak, those who made it into orbit reported a common epiphany upon seeing the entirety of Earth: that we must unify as a species to protect our only home. Half a century later, the world’s richest men fancy themselves astronauts, rendering that vantage point just another commodity.

the nation

A lista de mentiras e postagens absurdas de Allan dos Santos

 

de 

Felipe Neto

A lista de mentiras e postagens absurdas de Allan dos Santos, q acabou de ter a prisão preventiva decretada pelo STF, é absurda!

Vou tentar resumir algumas, mas são centenas, se não milhares, de postagens e vídeos nojentos.

🧶Segue uma pequena lista (quem tiver, pode mandar).

Allan dos Santos tentou de todas as formas dizer q a Covid19 era uma mentira, uma gigantesca conspiração mentirosa.

Ele foi amplamente apoiado pelo Olavo de Carvalho, que repetiu o mesmo discurso à exaustão.

Allan dos Santos disse, com todas as letras, que esconder o uso da cloroquina é igual a deixar judeus na dúvida entre chuveiro e câmara de gás

Allan dos Santos mentia muito. Mas muito.

Seguindo os ensinamentos do mestre Olavo de Carvalho, sempre utilizou a mentira para fazer o "lado do bem vencer a guerra".

O cara postou um vídeo falso que associava as FARC com o Lula e ameaçava Bolsonaro.

Allan dos Santos tb é contra a ciência, exatamente como o ídolo supremo, Olavo de Carvalo.

Aqui, ele defende a tese estúpida de Olavo de que a Terra é o centro do Universo e a ciência só diz q o Sol é o centro da Via Láctea pq é tudo uma conspiração contra Deus.

Quando o ministro da saúde de Bolsonaro, Luiz Henrique Mandetta, tornou-se um inimigo, Allan dos Santos fez isso aqui...

Publicou que ele havia gasto 25 milhões de reais em gel para lubrificação anal.

A informação é mentirosa, como sempre.

Querendo atacar as medidas de isolamento, Allan dos Santos pegou uma imagem dos protestos do "Black Lives Matter" e disse que era um protesto contra a CNN pela emissora promover o isolamento.

Isso não é um "erro", é uma fabricação de notícia falsa proposital.

Allan dos Santos achava q o bolsonarismo tinha vindo pra ficar e agora poderia promover seu sonho de transformar o Brasil em "The Handmaid's Tale".

Ele abertamente incita as pessoas a caçarem o q eles chamam de "comunistas".

Pra eles, comunista é td mundo q não é bolsonarista.

Quando o jogador Eriksen, da Dinamarca, teve um colapso e quase morreu durante uma partida, Allan dos Santos correu para informar que ele havia se vacinado e tinha chances do colapso ter sido culpa da vacina.

Tudo mentira. Eriksen ainda não tinha se vacinado.

Final de 2020, Allan dos Santos publicou um vídeo ameaçando o Ministro do STF Luís Roberto Barroso.

Disse:

"De uma vez por todas Barroso, vira homem! Tira a porra do digital! E bota só terrorista! Pra você ver o que a gente faz com você. Tá na hora de falar grosso nessa porra!”

Allan dos Santos foi condenado por publicar um vídeo, em 2017, onde disse q a cineasta Estela Renner "estimulava o uso de maconha para criancinhas".

A informação, obviamente, é falsa.

Allan dos Santos deve indenizar cineasta a quem acusou de estimular maconha para crianças Além de Allan dos Santos, site Terça Livre também foi condenado por ofensas à cineasta Estela Renner. Para TJSP, houve calúnia e difamação                 

Allan dos Santos foi citado por Renan Calheiros, relator da CPI da Pandemia, como

"figura central na distribuição das fake news contra o combate à pandemia e a favor do tratamento precoce, entre outros pontos"

Relatório final da CPI vai indiciar extremista Allan dos Santos: saiba os crimesAllan dos Santos será apontando como a figura central na distribuição das fake news contra o combate à pandemiahttps://www.metropoles.com/colunas/guilherme-amado/relatorio-final-da-cpi-vai-indiciar-ex
Com tudo isso, é importante dizer q os 2 inquéritos no STF contra Allan tratam:

- Divulgação de fake news e ataques a integrantes da Corte.

- Atuação de uma milícia digital que trabalha contra a democracia e as instituições no país.

A prisão de Allan é decorrente DISSO.

he Human Costs of A I

  

 

 SUE  HALPERN

In 2015 a cohort of well-known scientists and entrepreneurs including Stephen Hawking, Elon Musk, and Steve Wozniak issued a public letter urging technologists developing artificial intelligence systems to “research how to reap its benefits while avoiding potential pitfalls.”To that end, they wrote, “We recommend expanded research aimed at ensuring that increasingly capable AI systems are robust and beneficial: our AI systems must do what we want them to do.”

More than eight thousand people have now signed that letter. While most are academics, the signers also include researchers at Palantir, the secretive surveillance firm that helps ICE round up undocumented immigrants; the leaders of Vicarious, an industrial robotics company that boasts reductions for its clients of more than 50 percent in labor hours—which is to say, work performed by humans; and the founders of Sentient Technologies, who had previously developed the language-recognition technology used by Siri, Apple's voice assistant, and whose company has since been folded into Cognizant, a corporation that provided some of the underpaid, overly stressed workforce tasked with “moderating”content on Facebook. 

Musk, meanwhile, is pursuing more than just AI-equipped self-driving cars. His brain-chip company, Neuralink, aims to merge the brain with artificial intelligence, not only to develop life-changing medical applications for people with spinal cord injuries and neurological disorders, but, eventually, for everyone, to create a kind of hive mind. The goal, according to Musk, is a future “controlled by the combined will of the people of Earth—[since] that's obviously gonna be the future that we want.”

It turns out, then, that the most significant takeaway from a letter warning of the potential dangers of artificial intelligence might be its insistence that AI systems “must do what we want them to do.”And what is that? Even now, just six years later, that list is too long to catalog. Most of us have encountered scripted, artificially intelligent customer service bots whose main purpose seems to be forestalling conversations with actual humans. We have relied on AI to tell us what television shows to watch and where to dine. AI has helped people with brain injuries operate robotic arms and decipher verbal thoughts into audible words. AI delivers the results of our Google searches, as well as serving us ads based on those searches. AI is shaping the taste profile of plant-based burgers. AI has been used to monitor farmers’fields, compute credit scores, kill an Iranian nuclear scientist, grade papers, fill prescriptions, diagnose various kinds of cancers, write newspaper articles, buy and sell stocks, and decide which actors to cast in big-budget films in order to maximize the return on investment. By now, AI is as ambient as the Internet itself. In the words of the computer scientist Andrew Ng, artificial intelligence is “the new electricity.”

In 2017 Ng summarized his vision in a valedictory post on the blogging platform Medium announcing his resignation from the Chinese technology company Baidu. “The industrial revolution freed humanity from much repetitive physical drudgery,”he wrote. “I now want AI to free humanity from repetitive mental drudgery, such as driving in traffic.”If freeing people from that sort of mental drudgery seems trivial in the face of, say, climate change and other current and impending global calamities, its real value will be to stakeholders in a global autonomous car market that is expected to grow to more than $809 billion this year and $1.38 trillion by 2025. Overall, according to a report from PriceWaterhouseCoopers, AI could add up to $15.7 trillion to the global economy by 2030. 

Such unbridled growth is not without other, less compensatory consequences. As Kate Crawford's trenchant Atlas of AI demonstrates again and again, artificial intelligence does not come to us as a deus ex machina but, rather, through a number of dehumanizing extractive practices, of which most of us are unaware. Crawford, a senior researcher at Microsoft and a cofounder of the AI Now Institute at NYU, begins her tour of the AI universe in Silver Peak, Nevada, looking at the “open, iridescent green ponds”of brine pumped out of North America's largest lithium mine. Lithium—the “li”in “li-ion”batteries—is an essential ingredient in our digital lives. Without it there are no laptop computers, no smart watches, no cell phones. “

The term ‘artificial intelligence’may invoke ideas of algorithms, data, and cloud architectures,”Crawford writes, “but none of that can function without the minerals and resources that build computing's core components.”She adds:

 Many aspects of modern life have been moved to “the cloud”with little consideration of these material costs. Our work and personal lives, our medical histories, our leisure time, our entertainment, our political interests—all of this takes place in the world of networked computing architectures that we tap into from devices we hold in one hand, with lithium at their core.

 Calling those networked computers “the cloud”is a perfect example of what Crawford sees as “the strategic amnesia that accompanies stories of technological progress.”While the metaphor invokes an image of data floating weightlessly in the sky, the reality is that the cloud takes up hundreds of thousands of acres of terrestrial real estate, typically located where electricity is cheap. (The world's largest data center, as of 2018, in Langfang, China, covers 6.3 million square feet, the equivalent of 110 football fields.) Cheap, of course, is a relative term. A study from researchers at McMaster University found that, if unchecked, the computing industry as a whole could account for 14 percent of all greenhouse emissions by 2040—“about half of the entire transportation sector worldwide.”

Some of this carbon intensity has been driven by the belief that everbigger datasets are essential to train machine learning algorithms in order to create workable AI systems. (Machine learning is a kind of artificial intelligence, in which algorithms sort through enormous amounts of data using statistical methods to make classifications and predictions; the assumption is that more data delivers more accurate outcomes.) When researchers from the University of Massachusetts Amherst calculated the carbon emissions required to build and train a single natural language processing system—which teaches computers to interpret and use everyday language—they determined that it was around five times the lifetime emissions of the average American car.

 In the early days of what we now think of as digital computing, natural language processing was the holy grail of artificial intelligence. It is central to what has become known as the Turing test, a method of determining if a machine has achieved human-level cognition, derived from the British mathematician Alan Turing's 1950 paper “Computing Machinery and Intelligence.”In its simplest formulation, the test posits that we will know that machines have achieved real intelligence once people are unable to figure out if they are conversing with a human or a machine.

 Leaving aside the inadequacy of the Turing test to actually determine intelligence, as well as its reductive understanding of what intelligence is, it's indisputable that natural language processing systems have made tremendous strides, especially in the past few years. It's now possible to have a rudimentary exchange with Amazon's Alexa device, though there is a good chance that Alexa's answers will be wildly off the mark or inane. (Also, Alexa has begun to initiate conversations, almost always to promote some aspect of Amazon-related commerce; to wit: “You may be running low on Stash Irish breakfast tea. Would you like to reorder?”) Google Translate can take words and phrases from Hmong, say, and switch them into Serbian—a triumph, but again, one with varying degrees of success. 

Recently, the OpenAI research institute released GPT-3, an updated iteration of its natural language processor. The acronym stands for Generative Pre-trained Transformer. It is “pre-trained”because its algorithms have already sorted through something like 570 gigabytes of text, finding the most statistically significant clusters of words. With only a few prompts, GPT- 3 is able to write short stories and essays. Not long after it was released, I asked it to compose an essay with the title “The Future of Humanity.”If one did not read the result too closely, it appeared to address the subject with an uncanny degree of sophistication. That's because it was, essentially, a collection of words and phrases one might expect to see in such an essay. Strung together, though, they were vacuous: 

There was a time when the future was certain. That time is now reaching its conclusion. The present, like everything else, will soon come to an end…. We are on the brink of a technological revolution that has the potential to eradicate human suffering while simultaneously bringing an end to our existence as a species

. Natural language processors like GPT are trained on millions of documents and datasets scraped from the Internet, including Wikipedia and the entire cache of emails seized from Enron employees during the bankruptcy proceedings against the company, which were later released online by the Federal Energy Regulatory Commission. Like pretty much everything on the Internet, they became fair game for machine learning research. In addition to raising questions about the privacy implications of sharing personal correspondence without consent, Crawford asks readers to consider other, sometimes subtle, ramifications of training AI systems in this way, since those systems will reflect the linguistic norms of their sources. “Text archives were seen as neutral collections of language, as though there was a general equivalence between the words in a technical manual and how people write to colleagues via email,”she writes. 

If a language model is based on the kinds of words that are clustered together, it matters where those words come from. There is no neutral ground for language, and all text collections are also accounts of time, place, culture, and politics. 

a crucial point, and one that begins to get at the ways that AI training models can replicate entrenched social and cultural biases.

 Bias is a complicated term, and it's a useful one to keep in mind when trying to understand how AI systems operate. For developers building machine learning systems, “bias”refers to the task they are building the AI to address, such as playing chess or making restaurant reservations. In that situation, it's neutral. More typically (and colloquially), it not only describes AI systems that perpetuate prejudices and trade on stereotypes but also suggests how they got this way. Machines only know what they know from the data they have been given.

 Historical data, for example, has the built-in problem of reflecting and reinforcing historical patterns. A good example of this is a so-called talent management system built a few years ago by developers at Amazon. Their goal was to automate the hiring of potential software engineers with an AI system that could sort through hundreds of résumés and score them the way Amazon shoppers rate products. The AI selected the highest scorers and rejected the rest. But when the developers looked at the results, they found that the system was only recommending men. This was because the AI system had been trained on a dataset of Amazon résumés from employees the company had hired in the past ten years, almost all of whom were men. 

In his surprisingly lively examination of AI regulation, We, the Robots? , the legal scholar Simon Chesterman points to an audit of another résumé-screening program that found that “the two most important factors indicative of job performance…were being named Jared and having played high school lacrosse.”Bias can be inadvertently introduced into AI systems in other ways, too. A study that looked at the three major facial recognition systems found that they failed to identify gender just 1 percent of the time when the subject was a white male. When the subject was a darker-skinned female, however, the error rate was nearly 35 percent for two of the companies, and 21 percent for the third. This was not a mistake. The algorithm builders trained their algorithms on datasets composed primarily of people who looked like them. In so doing, they introduced bias into the system.

The consequences of these kinds of errors can be profound. They have caused Facebook to label Black men as primates, they could cause autonomous vehicles to fail to recognize a woman with dark skin crossing the street, and they could lead the police to arrest the wrong man. In fact, last year The New York Times reported on the case of Robert Williams, a Black man who got a call from the Detroit police while he was at work, telling him to report to the police station to be arrested. At the station, Williams was taken into an interrogation room, where detectives showed him three grainy photographs. These turned out to be surveillance photos from a store where someone had stolen nearly $4,000 of merchandise. The person in question was a heavyset Black man, like Williams. But that is where the similarities ended. How had the police department's computer identified Williams? Through a match between the grainy surveillance photos and Williams's driver's license photo. In this case, a badly trained facial recognition system was used to arrest an innocent man and toss him in jail, even though there was no physical evidence connecting him to the crime. 

Databases used by law enforcement include about 641 million driver's license and ID photos from twenty-one states. In many states, personal information collected by municipal agencies like the Department of Motor Vehicles is for sale to third parties and can then be incorporated into commercial facial recognition systems. Crawford points out that mug shots, too, have been fair game: “A person standing in front of a camera in an orange jumpsuit, then, is dehumanized as just more data,”she writes. 

And like a tightening ratchet, the faces of deceased persons, suspects, and prisoners are harvested to sharpen the police and border surveillance facial recognition systems that are then used to monitor and detain more people.

 Artificial intelligence systems are now a staple of the criminal justice system. In some jurisdictions, like Los Angeles, AI helped determine where the police should patrol, a determination that is often made on the basis of where the most crimes are committed. That might sound reasonable, but sending more police to patrol those neighborhoods has resulted in more people being arrested for nonviolent, minor offenses. It becomes a self-reinforcing loop: the more crime, the more police; the more police, the more crime—and on and on. Then, once someone is arrested, a judge may use risk assessment software in deciding if they should go to jail and for how long. If the arrestee lives in a high-crime neighborhood, they are much more likely to get jail time, because the algorithm is not simply assessing their propensity to commit another crime—which, of course, it cannot know—it is looking at the criminal records of an aggregate of people with similar backgrounds and characteristics.* 

Judges, prosecutors, and parole boards who use these kinds of risk assessment tools often believe that they are fairer than decisions made by humans, failing to see that, in reality, the assessments have been made by the humans who designed these AI systems in the first place. Additionally, as Chesterman notes, a Canadian study

 of lawyers and judges…found that many regarded [risk assessment] software…as an improvement over subjective judgment: though risk assessment tools were not deemed especially reliable predictors of future behaviour, they were also favoured because using them minimized the risk that the lawyers and judges themselves would be blamed for the consequences of their decisions. 

Other kinds of bias are even more subtle. Many AI systems are proprietary. Shielded behind intellectual property laws, they are often opaque, even to the people employing them. They are similarly inscrutable to the population at large. Consider credit scores: for most of us, this is a number lurking in the background, not just of our financial lives but of what our financial lives lead to, like mortgages and spending limits on credit cards. In the past, a credit score was typically a reflection of how conscientiously one paid bills and settled debts. Now there is talk of enhancing this with “alternative”data, culled from social media and the Internet.

There is no way to know where all the data is coming from, if it's accurate, how it's weighted, or whether the algorithmic engine powering the system is relying on data that itself replicates historical prejudices, like where someone lives or where they went to college. Moreover, while it may be illegal in certain circumstances to ask for some personal information, like gender, algorithms can be riddled with assumptions—made by their human authors—such as that an elementary school teacher is female or a commercial pilot is male. They may also use one variable as a proxy for another, such as zip code for wealth or surname for race and ethnicity.

 Not long ago, the online insurance company Lemonade posted a series of tweets “explaining”how the company's algorithms assess claims. As reported by the website Recode , Lemonade maintained that it collected more than 1,600 data points on each user, but

didn't say what those data points are or how and when they're collected, simply that they produce “nuanced profiles”and “remarkably predictive insights”which help Lemonade determine, in apparently granular detail, its customers’level of risk. 

Risk, here, actually refers to the company's level of risk, which it aimed to mitigate by requiring customers making insurance claims to submit videos that its AI “carefully analyzes…for signs of fraud,”including “non-verbal cues.”The Twitter thread concluded that Lemonade's AI was responsible for the company making more money in premiums than it had to pay out in claims.

 Lemonade's use of video to assess a client's truthfulness is part of a new trend involving the use of AI to “read”human emotions. Ostensibly, “affective AI”can scan a face and “know”how a person is feeling. One of the leaders in this field, a company called Affectiva, claims it is “humanizing technology.”Pitching its service to companies that hope to gauge consumer interest in their products, Affectiva says that it can measure a person's moment-by-moment micro-facial expressions as they view an advertisement, using “the world's largest emotion database,”and correlate these microscopic twitches with human attributes like trustworthiness and attentiveness. Affective AI systems are now used by airport screeners to “identify”terrorists, universities to assess student engagement, corporations to weed out job candidates. 

How does the AI know if someone is bored or grief-stricken or euphoric? Affective AI is rooted, first, in an assumption that there is a shared taxonomy of facial expressions, and second, in the idea that that taxonomy can be translated into a numerical system. Is this specious? At least one study, from the University of Maryland, has shown that Black faces are more likely than white faces to be classified by AI as angry. And, of course, there's the surveillance issues that this raises, and the many ways surveillance leads to self-censorship and the curtailment of self-expression. 

This, though, is not usually what people fear about artificial intelligence. More often it's replacement—that AI will supersede us intellectually, or that it will take our jobs. The concern about employment is not misplaced. According to a team of economists from MIT and Boston University, automation has been subsuming jobs faster than it is creating them. Another study, from the forecasting firm Oxford Economics, predicts the loss of 20 million jobs to automation by 2030. The prospect that we will soon work for our machines, and not the other way around, is already the norm at Amazon warehouses, where humans are, in Crawford's words, “there to complete the specific, fiddly tasks that robots cannot.”But even before Amazon's unprecedented dehumanization project, AI developers were reliant on legions of underpaid scut workers to tag audio clips and label images, among other things. “Exploitative forms of work exist at all stages of the AI pipeline,”Crawford writes, 

from the mining sector…to the software side, where distributed workforces are paid pennies per microtask…. Workers do the repetitive tasks that backstop claims of AI magic—but they rarely receive credit for making the systems function. 

AI is cannibalizing the white-collar sector, too. A study from Wells Fargo estimates that as many as 200,000 finance jobs will disappear in the next decade. AI now reads legal documents with a speed and accuracy unmatched by its human counterparts, generates corporate reports, and is responsible for hiring, assessing, and firing workers. AI is also moving into creative fields like musical composition. Aiva (Artificial Intelligence Virtual Artist) has learned music theory from a database of classical compositions, produces its own sheet music, contributes to movie soundtracks, and is the first AI to be officially designated as a composer, with its own copyright under the France and Luxembourg authors’rights society. 

But the years ahead won't all be about loss, as Kevin Roose points out in his ultimately genial assessment of the prospect of our coexistence with automated and artificially intelligent machines, Futureproof: 9 Rules for Humans in the Age of Automation . Aside from the potential savings from the added efficiencies and reduced labor costs associated with automation, which may or may not be passed along to consumers but will certainly accrue to corporations and their owners (among them, the richest person in the world, Amazon founder Jeff Bezos), there will be new jobs in fields that don't yet exist. Cognizant, the company that supplied Facebook with content moderators, imagines some of them to be “personal data brokers,”“augmented reality journey builders,”and “juvenile cyber-crime rehabilitation counselors.”And then there's this: The Wall Street Journal recently reported that Pepper, a humanoid robot created by the SoftBank group in Japan, was so incompetent at the various jobs for which it was
tasked, among them Buddhist priest and nursing home attendant, that the company stopped making it, which suggests that some humans may not be obsolete yet.

 The other fear—that AI systems will acquire human-level intelligence and eventually outwit us—remains, thus far, the stuff of science fiction. True, AI can perform certain functions more quickly and accurately than people, but that is hardly a measure of intelligence. In the estimation of the computer scientist and AI entrepreneur Erik J. Larson, “As we successfully apply simpler, narrow versions of intelligence that benefit from faster computers and lots of data, we are not making incremental progress, but rather picking low-hanging fruit.”His thoughtful new book, The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do , makes a convincing case that artificial general intelligence—machine-based intelligence that matches our own—is beyond the capacity of algorithmic machine learning because there is a mismatch between how humans and machines know what they know. Human knowledge is diverse, as are our capacities. Our intelligence derives from the range of our experiences and thrives, at times, on the irrational, the serendipitous, the spiritual, the whimsical. In the estimation of the French machine learning scientist François Chollet, Larson writes, “Your brain is one piece in a broader system which includes your body, your environment, other humans, and culture as a whole.”

By contrast, even machines that master the tasks they are trained to perform can't jump domains. Aiva, for example, can't drive a car even though it can write music (and wouldn't even be able to do that without Bach and Beethoven). AlphaGo can best the most accomplished Go player in the world, but it can't play chess, let alone write music or drive a car. Machine learning systems, moreover, are trained on datasets that are, by definition, limited. (If they weren't, they would not be datasets .) As Larson notes, the real world—the one we inhabit and interact with—generates data all day long: “Common sense goes a long way toward understanding the limitations of machine learning: it tells us life is unpredictable.”AI can't account for the qualitative, nonmeasurable, idiosyncratic, messy stuff of life. The danger ahead, then, is not that artificially intelligent systems will get smarter than their human creators. It's that by valorizing these systems without reservation, humans will voluntarily cede the very essence of our-selves—our curiosity, our compassion, our autonomy, our creativity—to a narrow, algorithmically driven vision of what counts. 

*A 2016 ProPublica study of more than seven thousand arrests in Broward County, Florida, found that the county's AI system was twice as likely to label Black defendants future criminals than whites. One of the questions it used to assess risk was “Was one of your parents ever sent to jail or prison?,”thus perpetuating mass incarceration. Adam Harvey/Anastasia Kubrak ■

Dottie Dodgion, a Standout Drummer in More Ways Than One, Dies at 91

 At a time when a female jazz percussionist was a rarity, she played with Benny Goodman. She went on to work with Marian McPartland and other big names.

By Richard Sandomir

Dottie Dodgion, one of the very few high-profile female drummers in the male-dominated jazz world of the 1950s and ’60s, died on Sept. 17 in a hospice center in Pacific Grove, Calif. She was 91.

The cause was a stroke, said her daughter and only immediate survivor, Deborah Dodgion.

Ms. Dodgion, who was known for her steady and swinging but unobtrusive approach to the drums, worked for more than 60 years with some of the biggest names in jazz, including Benny Goodman, Marian McPartland and Ruby Braff. She also led her own combos. But she rarely recorded.

“She didn’t get the exposure that she might have gotten through recording because of her gender,” said Wayne Enstice, who collaborated with her on her autobiography, “The Lady Swings: Memoirs of a Jazz Drummer” (2021). “She wasn’t taken as seriously as she should have been — not by other musicians, but by people on the business side.”

Unlike some drummers, Ms. Dodgion was more concerned with keeping the beat than with calling attention to herself.

“There’s no denying that many drummers love the spotlight,” she wrote in her autobiography. “That’s why I sometimes say I’m not a ‘real drummer.’”

She rarely took solos, she wrote, and when she did solo her approach “came from being a singer. I’d hear the melody inside my head so the rhythms I laid down always followed the song form of whatever tune I played.”

She continued to play until she was 90, with her own trio, on Thursday nights at the Inn at Spanish Bay in Pebble Beach, near her home in Pacific Grove — a gig that lasted 14 years. After breaking a shoulder in 2019, she sang while another drummer, Andy Weis, filled in for her, until the coronavirus forced the hotel to shut down temporarily.

“She swung hard — and that meant there was a lesson to be heard in watching her play,” Mr. Weis said by phone. “She knew exactly what tempo would swing the hardest.”

The celebrated jazz drummer Terri Lyne Carrington recalled that she had begun playing drums at 7 and first saw Ms. Dodgion about two years later at a women’s jazz festival. As far as Ms. Carrington knew at the time, Ms. Dodgion was the only female drummer around.

“She always had a beautiful time feel, which is the most important part of being a drummer,” Ms. Carrington said in a phone interview. “She was never the fanciest, trickiest drummer in the world who dazzled with solos, but she really captured the essence of being a drummer.”

Dorothy Rosalie Giaimo was born on Sept. 23, 1929, in Brea, Calif. Her father, Charles, was a drummer. Her mother, Ada (Tipton) Giaimo, aspired to be a dancer but became a waitress after her husband left the family when Dottie was 2.

One day, when she was 5, her father stopped by her grandparents’ house in Los Angeles, where she was living, and, as she said, “kidnapped” her, taking her on the road for two years to the hotels, road houses and strip joints where he led a band. Absorbing the sounds and rhythms of her father’s drumming was her introduction to show business, albeit against her will. She was 7 when she returned to her mother, who had remarried.

Her stepfather, a chicken farmer, raped Dottie when she was 10; he was convicted and sentenced to 20 years in prison. After she and her mother moved to Berkeley, Calif., Dottie found peace in her weekend bus trips to San Francisco to see her father’s band at a strip club, Streets of Paris.

“His excellent time attracted all the best strippers,” she wrote.

As a teenager, she sang at private parties and weddings, which led to work in the mid-1940s with bands led by the jazz guitarist Nick Esposito and the renowned bassist Charles Mingus. Singing eventually gave way to drumming, which she picked up by listening to her father, and through the 1950s she played in clubs in Los Angeles, San Francisco and Nevada. For a time, she was the house drummer at Jimbo’s Bop City in San Francisco.

Meeting the bassist Eugene Wright, who would become an integral part of the Dave Brubeck Quartet, had a transformative effect on how she viewed her role in a band.

“Eugene coached me on the nuances of playing in a rhythm section,” she wrote, “including the intangible insides on how to fit with the piano and the bass.”

Ms. Dodgion’s first marriage, to Robert Bennett, was annulled; her marriages to Monty Budwig, a bassist, and Jerry Dodgion, a saxophonist, ended in divorce.

With Mr. Dodgion, who was in Benny Goodman’s band, Ms. Dodgion moved to Manhattan in 1961. On their first day there, the band rehearsed for an engagement at Basin Street East. Ms. Dodgion dropped her husband off; when she returned at the end of the rehearsal, she was surprised when Goodman, who was looking for a new drummer, asked her to sit in with the band.

“I thought it was just a jam session,” she told The New York Times in 1972. “Benny’d call out a number — ‘Gotta Be This or That’ — and I’d start looking for the music. But he’d say, ‘Don’t open the book.’ Every tune, it was the same — ‘Don’t open the book.’ At the end of the rehearsal, Benny said: ‘See you tonight, Jerry. You, too, Dottie.’ That was how I found out I was going to play with the band.”

Ten days into the engagement at the club, Goodman forgot to introduce her when he name-checked some other members of his 10-piece band. When the crowd demanded that he announce her name, he relented, and she received a standing ovation. But as she left the bandstand, she later recalled, Goodman’s manager whispered “’Bye” in her ear, indicating that she was being fired for getting more applause than her boss.

She was not out of work for long. She quickly got a job with Tony Bennett at the Waldorf-Astoria Hotel. Over the next 40 years, she played with Marian McPartland, Ruby Braff, Zoot Sims, Wild Bill Davison, Joe Venuti and others.

“She could adapt from swing to bop, to Latin rhythms, all without calling attention to herself,” Mr. Enstice said. “She could fit in with anyone.”

Ms. Dodgion worked with Ms. McPartland in 1964 and again 13 years later, when Ms. McPartland led an all-female band.

“Dorothy had a natural sense of swing,” Ms. McPartland told The Sacramento Bee in 1989. “She keeps steady time and she swings — those are the most important things for a good drummer.”

THE NEW YORK TIMES