O PCC (Primeiro Comando da Capital) criou um sistema de tributação de crimes e chegou a cobrar até R$ 250 por mês de seus integrantes para sustentar suas atividades. O esquema foi revelado pelo delegado Ricardo Hiroshi Ishida, da PF (Polícia Federal), responsável por investigações sobre crime organizado em Curitiba. Ishida acompanhou nesta manhã a operação Cravada, que visa desarticular a rede de financiamento da facção criminosa e prendeu 20 pessoas em sete estados. "É como se houvesse um sistema de tributação do crime", afirmou o delegado, descrevendo o financiamento do PCC. "Se pegarmos um salário mínimo de hoje [R$ 998], 25% desse valor iria para essas contribuições para a facção criminosa", explicou.
De acordo com o delegado da PF Martin Bottaro Purper, coordenador da operação Cravada, a estimativa é que o PCC obtinha até R$ 1 milhão por mês com essas contribuições. Esse valor era distribuído por cerca de 400 contas bancárias para evitar seu rastreamento e, de lá, saia para financiar compra de armas, drogas, pagamento de despesas de familiares de membros da quadrilha e para remunerar lideranças.
"Eles arrecadam valores em rifas ou mensalidades. Esse valor sai da base e chega para os líderes, que administram o dinheiro", disse Purper. "Tudo é feito para que os líderes tenham bastante dinheiro, a base sustente e vários crimes sejam cometidos com ajuda do financiamento". Segundo a PF, toda a contabilidade era era feita pelos próprios presos de dentro dos presídios. Na operação Cravada, a PF constatou que funcionava no presídio estadual de Piraquara, na região metropolitana de Curitiba, uma espécie de central de administração dos recursos.
(...)
O superintendente regional da PF no Paraná, o delegado Luciano Flores, disse que as mais de 400 contas bancárias usadas pelo PCC foram bloqueadas por ordem judicial. Ele espera que a operação e o bloqueio sirva para "asfixiar os meios de financiamento da facção". "Que o dinheiro deixe de circular e financiar crimes violentos", afirmou.
Fonte: Aqui
Mais sobre a contabilidade do PCC aqui e aqui.
06 agosto 2019
Introdução à Contabilidade | Prof. Odair Correa
Eu fico muito feliz ao ver o pessoal da minha turma de mestrado conquistando o mundo por aí. Hoje o Odair nos enviou um vídeo, pois está adentrando o mundo do ensino a distância. No vídeo ele faz uma excelente introdução à contabilidade.
Sucesso, amigo querido! Você nasceu pra isso!!
05 agosto 2019
Siga o dinheiro
Um documento do Centro Stigler (via aqui) mostra que a crítica ao uso do rastreamento financeiro para descobrir o foco do terrorismo pode ser inadequado. O documento mostra que é possível reduzir os ataques de terroristas a partir de um estudo realizado no Paquistão.
Primeiro, o financiamento do terrorismo afeta o tipo de ataque terrorista que estão sendo planejados. (...) Em segundo lugar, [há] aumento dos ataques que está ligado aos grupos terroristas que desfrutam de um aumento no financiamento.
Outra situação foi revelado pelo ProPublica e WSJournal (via aqui) que alguns pais evitam o custo das mensalidades da faculdade nos EUA. Em alguns lugares, há ajuda financeira para os “necessitados”. Os país, para obterem este tipo de ajuda, “desistem” da custódia dos filhos. E assim, podem se qualificar para auxílios. Este tipo de fraude ocorre pelo fato do custo da educação estar aumentando nos últimos anos.
03 agosto 2019
Big Data e Pesquisa em Ciências Humanas/Sociais
As vantagens são: big, always-on e não reativo. O que significa isto? Segundo Salganik, o fato de termos um grande número de dados permite que o pesquisador possa estudar eventos que são raros, estudar a heterogeneidade de maneira mais completa (eu posso pesquisar o homem branco, que vive em Brasília, com idade de 20 anos e que torce para o América de Natal) e conseguir detectar diferenças que são pequenas. A segunda grande vantagem é o fato de estar constantemente coletando informações. Se uso o Twitter para saber como as pessoas estão pensando sobre a economia, posso fazer uma pesquisa com as últimas mensagens que foram postadas. Finalmente, a base de dados onde podemos obter um grande número de informações geralmente são não reativas. Ou seja, o comportamento das pessoas não muda por estarem sendo observadas ou suas opiniões não se alteram na frente de um pesquisador. Assim, uma pessoa que está pesquisando no "search" do Google tenderá a ser mais verdadeiro que aquela pessoas diante de uma questão de uma pesquisa (vide o que diz o livro Todo Mundo Mente)
Mas o uso do big data em pesquisa possui sete inconvenientes. Alguns dos problemas apontados podem ser solucionados. Mas não deixam de representar um risco para qualidade da pesquisa. Os problemas são: incompletude, inacessibilidade, não representatividade, drifting, influenciado pelo algoritmo, sujeira e o fato de ser sensível. Em geral informações derivadas de big data não foram feitas para a sua pesquisa.Isto significa dizer que nem toda informação estará disponível. Se desejo saber o efeito da raça na escolha de um time de futebol, talvez não tenha esta informação no Facebook. Assim, o big data geralmente é falho nas informações demográficas. É possível resolver parte deste problema com técnicas, como imputação ou fazendo cruzamento de bases diferentes.
Um segundo problema é a inacessibilidade. Poucos pesquisadores possuem acesso da base de dados do Facebook. E quando conseguem este acesso, precisam fazer compromissos que podem prejudicar a pesquisa. A questão da inacessibilidade é muito menos uma barreira tecnológica do que problemas legais, éticos e de negócios.
Grande número de dados é bom para pesquisa, mas muitas vezes eles não representam a população de maneira adequada. A não representatividade faz com que uma pesquisa usando as postagens do Twitter não sejam representativos já que está restrito as pessoas que possuem conta nesta rede social e utilizam de maneira regular. Assim como Salganik, não acredito que isto seja um empecilho para pesquisa. O autor faz uma discussão importante ao lembrar que dificilmente uma amostra da população consegue ser realmente representativa em todos os aspectos.
Drifting significa aqui mudança. Grandes bases de dados precisam lidar com mudanças na forma como as pessoas usam um sistema, que pessoas usam o sistema e com as mudanças do sistema. Parece-me que o Facebook teve, ao longo do tempo, este tipo de mudança: inicialmente, a rede social no Brasil era predominantemente habitada por jovens; com o tempo, pessoas mais idosas passaram a se cadastrar na rede. Muitos jovens transferiram sua preferência para o Instagram, nos anos recentes. Este tipo de mudança pode alterar os resultados coletados com dados do Facebook, por exemplo.
Uma mudança técnica ocorre no próprio algoritmo. Recentemente, uma rede social passou a não divulgar mais o número de likes em cada postagem. Isto naturalmente afeta os dados coletados nesta rede social. Este problema é importante, já que muitos sites estão mudando constantemente sua configuração, procurando maximizar o tempo de navegação do usuário no mesmo. Se estas mudanças não estão documentadas, podem influenciar os resultados obtidos nas pesquisas.
As fontes de um grande número de dados geralmente são sujas. Ou seja, são afetadas por porcarias, como spam. O número de hastags pode ser manipulado por robôs e isto tem sido feito com bastante frequência. Mesmo uma Wikipedia pode ser editada, apesar dos controles existentes para evitar manipulações nos verbetes.
Finalmente, o Big Data é uma informação sensível. Imagine que deseja verificar o volume de pesquisa da minha universidade através do uso da rede existente lá. Se o objetivo da pesquisa é procurar saber quais as áreas que estão sendo objeto de interesse por parte dos alunos e docentes, o endereço da internet que está sendo consultado agora pode representar uma fonte de informação valiosa. Entretanto, com este tipo de informação, a pesquisa irá descobrir que muitas pessoas usam a rede para assistir um filme na Netflix, ou um jogo de futebol ou até um site pornográfico. A informação obtida pode revelar preferências sexuais e ideológicas, dados pessoais que podem constranger as pessoas. Isto explica a inacessibilidade deste tipo de informação.
50 anos da Revolução de Ball e Brown na contabilidade
In the early to mid 1960s, the finance world had a very low opinion of accounting, particularly in terms of financial statement information. The generally accepted wisdom was that such accounting was of no value in the assessment of a business’s worth, and was therefore completely unrelated to such investment matters as stock prices. It’s an attitude that seems absurd today.
The respect in which accounting is currently held is partly due to the work done by two young Australians at the University of Chicago. One was Philip Brown. The other was Ray Ball, who arrived at the university’s hallowed halls a few years after Brown.
“When I arrived the place just crackled with ideas,” Ball, who was four-and-a-half years younger than Brown, says.
“You would walk into the faculty lounge and say something and someone would immediately get up and start writing on the blackboards, trying to dissect the idea, pull it apart and play with it.
[...]
The idea that Ball and Brown challenged was the one around the value of accounting. The lowly opinion of the profession came from the fact that, at the time, there were so many different methods accountants could choose to produce various financial results. It led to the belief that number crunchers were simply employed to hoodwink investors or creditors.
This was a serious issue at the time. An academic paper written by another Australian accounting heavyweight, R.J. Chambers, concluded that from a single set of organisational transactions, the various accounting methods available meant it was possible to report 30 million different profit figures. Another problem was historical-cost accounting, which did not take inflation into account and therefore, on balance sheets, did not compare like with like.
Ball and Brown believed that accounting would never have played such a central role in business and finance for so many centuries if it truly lacked value and meaning.
They decided to run a study, which, put very simply, would find out whether and how share prices had reacted to information captured in financial statements in the past. The pair did so by crunching big data, and the data really was big. The computer (the only one at the University of Chicago) filled two rooms!
“It took up an enormous space, but the size of its memory was one two-millionth the size of my iPhone’s memory,” smiles Ball, who is now the Sidney Davidson Distinguished Service Professor of Accounting at the University of Chicago Booth School of Business.
“When one person was running a job on it, nobody else in the university could do any computing. The file of historical stock returns was on magnetic tape that took three minutes for the computer to read from one end to the other.”
The results of their study empirically demonstrated for the very first time that accounting figures were of immense value to investors. Accounting reports, such as annual reports, profit reports and profit warnings, correlated directly with shifts in stock prices.
Also, the now famous “Figure 1” graph in their published paper – “Ball and Brown (1968): An Empirical Evaluation of Accounting Income Numbers” – clearly illustrated the fact that the market anticipated profit reports, building value into a stock (or taking it away) in the lead-up to a report, as well as responding with a rise or fall in value after a report’s release.
The article was originally rejected by The Accounting Review, partly because it was all but impossible to find a referee with the knowledge to handle the submission, but also because editors felt it had “little to do with accounting”.
However, in 1968, when Nicholas Dopuch (also remembered as a transformational figure in accounting research) was appointed as editor of The Journal of Accounting Research, the study finally earned its place in history.
The result
In the pre-internet era, news didn’t spread quickly. Ball and Brown returned to Australia and got on with their lives. Academics mostly reacted to their paper with indifference. The typical financial academic, Brown says, went on believing financial statement information meant nothing. Still, in the absence of the two young Australians, their research study took on a life of its own.
As more academics cited “Ball and Brown (1968)” in their own work, people began to take notice. Eventually, those in the academic and financial realms recognised the work as a true classic.
“Overall, ‘Ball and Brown (1968)’ expressed a view of information in markets that was new to the accounting literature, and contributed to a sea change in attitudes toward financial markets, disclosure, and financial reporting,” the pair wrote in a 2014 paper called “Ball and Brown (1968): A Retrospective”, published in The Accounting Review.
“Viewed more generally, the research demonstrated that accounting is a viable area for market-based and information-economics reasoning, at a time when these areas were just being developed. It helped elevate the status of accounting research among colleagues in adjacent areas and in universities generally. We are fortunate and proud to have authored it.”
The respect in which accounting is currently held is partly due to the work done by two young Australians at the University of Chicago. One was Philip Brown. The other was Ray Ball, who arrived at the university’s hallowed halls a few years after Brown.
“When I arrived the place just crackled with ideas,” Ball, who was four-and-a-half years younger than Brown, says.
“You would walk into the faculty lounge and say something and someone would immediately get up and start writing on the blackboards, trying to dissect the idea, pull it apart and play with it.
[...]
The idea that Ball and Brown challenged was the one around the value of accounting. The lowly opinion of the profession came from the fact that, at the time, there were so many different methods accountants could choose to produce various financial results. It led to the belief that number crunchers were simply employed to hoodwink investors or creditors.
This was a serious issue at the time. An academic paper written by another Australian accounting heavyweight, R.J. Chambers, concluded that from a single set of organisational transactions, the various accounting methods available meant it was possible to report 30 million different profit figures. Another problem was historical-cost accounting, which did not take inflation into account and therefore, on balance sheets, did not compare like with like.
Ball and Brown believed that accounting would never have played such a central role in business and finance for so many centuries if it truly lacked value and meaning.
They decided to run a study, which, put very simply, would find out whether and how share prices had reacted to information captured in financial statements in the past. The pair did so by crunching big data, and the data really was big. The computer (the only one at the University of Chicago) filled two rooms!
“It took up an enormous space, but the size of its memory was one two-millionth the size of my iPhone’s memory,” smiles Ball, who is now the Sidney Davidson Distinguished Service Professor of Accounting at the University of Chicago Booth School of Business.
“When one person was running a job on it, nobody else in the university could do any computing. The file of historical stock returns was on magnetic tape that took three minutes for the computer to read from one end to the other.”
The results of their study empirically demonstrated for the very first time that accounting figures were of immense value to investors. Accounting reports, such as annual reports, profit reports and profit warnings, correlated directly with shifts in stock prices.
Also, the now famous “Figure 1” graph in their published paper – “Ball and Brown (1968): An Empirical Evaluation of Accounting Income Numbers” – clearly illustrated the fact that the market anticipated profit reports, building value into a stock (or taking it away) in the lead-up to a report, as well as responding with a rise or fall in value after a report’s release.
The article was originally rejected by The Accounting Review, partly because it was all but impossible to find a referee with the knowledge to handle the submission, but also because editors felt it had “little to do with accounting”.
However, in 1968, when Nicholas Dopuch (also remembered as a transformational figure in accounting research) was appointed as editor of The Journal of Accounting Research, the study finally earned its place in history.
The result
In the pre-internet era, news didn’t spread quickly. Ball and Brown returned to Australia and got on with their lives. Academics mostly reacted to their paper with indifference. The typical financial academic, Brown says, went on believing financial statement information meant nothing. Still, in the absence of the two young Australians, their research study took on a life of its own.
As more academics cited “Ball and Brown (1968)” in their own work, people began to take notice. Eventually, those in the academic and financial realms recognised the work as a true classic.
“Overall, ‘Ball and Brown (1968)’ expressed a view of information in markets that was new to the accounting literature, and contributed to a sea change in attitudes toward financial markets, disclosure, and financial reporting,” the pair wrote in a 2014 paper called “Ball and Brown (1968): A Retrospective”, published in The Accounting Review.
“Viewed more generally, the research demonstrated that accounting is a viable area for market-based and information-economics reasoning, at a time when these areas were just being developed. It helped elevate the status of accounting research among colleagues in adjacent areas and in universities generally. We are fortunate and proud to have authored it.”
Fonte: aqui
02 agosto 2019
Atividades do Iasb
Novo Representante do Brasil no Board do Iasb
Mr Cendon has almost three decades of experience in auditing and consulting. He joins the Board from PwC Brazil Accounting and Consulting Services, where he has worked as Partner responsible for providing accounting advice to audit teams and multinational companies reporting under IFRS Standards. He has also served as the Director for Professional Development at the Brazilian Institute of Independent Auditors (IBRACON).
Ou seja, Cendon é originário de uma Big Four. Seu mandato deve ir até julho de 2024
Desfile da Victoria´s Secret
 |
| Adriana Lima se despedindo em seu último desfile, em 2018 |
[...] o desfile da Victoria’s Secret não acontecerá este ano. A informação ainda não foi confirmada pela grife, que já havia comunicado em maio que a apresentação de 2019 não seria televisionada pela primeira vez em quase duas décadas.
Sendo confirmada ou não, a possibilidade do show acabar representa o fim de uma era: o evento acontecia anualmente desde 1995 e ao, longo do tempo, se transformou no maior acontecimento do business, com apresentações apoteóticas de celebridades como Rihanna e Justin Bieber. Ser eleita uma Angel era o ápice da carreira de uma modelo.
A marca, no entanto, já vinha sendo amplamente criticada pela falta de diversidade na passarela. Enquanto novas grifes de lingerie como a Savage X Fenty, comandada por Rihanna, celebram todos os tipos de mulheres e corpos, a VS seguia presa ao seu próprio padrão de beleza, completamente ultrapassado. [...]
A polêmica declaração de Razek é o perfeito retrato de que a Victoria´s Secret não tem olhado para o mundo ao seu redor, presa a seu antigo case de sucesso, que ficou ultrapassado. O desfile fazia sentido em uma época que a moda valorizava um único padrão de beleza. Mas – finalmente! – a indústria mudou. Estamos vivendo um novo momento, que celebra a diversidade, a personalidade, homens e mulheres reais. O consumidor passou a ter voz ativíssima, nada mais é imposto. [...]
A própria audiência do desfile já havia sofrido um enorme impacto: ao longo dos últimos anos, os expectadores caíram de 9,7 milhões de pessoas (2013) para 3,3 milhões (2018). [...]
O descontentamento com a marca já podia ser sentido também nas vendas: em 2018, as ações da L Brands caíram 41% devido à desaceleração das vendas na Victoria´s Secret. No mesmo ano, foram fechadas 30 lojas da marca – para 2019, a previsão é que outros 53 endereços encerrem as atividades. “O problema vai muito além do desfile em si”, pondera Ju Ferraz, colunista do Vogue Gente. [...]
Fundada nos anos 70, a Victoria´s Secret nasceu em meio a uma revolução sexual (a pílula anticoncepcional havia chegado ao mercado na década anterior) e foi um importante marco para a época, uma das primeiras marcas a vender lingerie tão abertamente, em lojas dedicadas exclusivamente à roupa íntima – era empoderador (e sexy) ter controle sobre o próprio corpo.
“Já nos anos 90, as supermodels agregavam à marca de underwear um status que nenhuma outra teve no mundo”, relembra Pedro Sales, diretor de moda da Vogue. “Ganhando fortunas, Gisele, Stephanie Seymour e Naomi riscavam a passarela, ovacionadas como grandes artistas do showbiz. No Brasil, fazer parte do casting foi o sonho de muitas meninas, que viam em modelos como Adriana Lima, Alessandra Ambrosio e Lais Ribeiro uma carreira cheia de fama e altos cachês.”
[...] Mas o mundo mudou e a Victoria´s Secret se afundou no próprio case que criou, hoje antiquado.”
Em 1982 a The Limited (L Brands, atualmente) comprou a Victoria’s Secrets por US$ 1 milhão. Les Wexner, dono da marca, é hoje a 413ª pessoa mais rica do mundo, segundo a Forbes.
01 agosto 2019
Gerenciamento de Impressão
The aim of this study is to investigate the evidence of impression management in terms of selectivity or improved presentation in the graphs and charts used by companies. The reports of 180 Brazilian companies between 1997 and 2014 were analysed. The variables tested were: company size, profitability, age, variation in results, report size and publication period. The results indicated that there is a significantly positive relationship between financial performance and the total amount of graphs and charts, in particular those with key financial information (net income, net revenue and dividends) and those with improved or enhanced presentation. This is a sign of impression management in the reports analysed. It was verified a relationship between the company’s age and the low amount of graphs and charts used by the company during the initial years of the analysis period to disclose financial information in their reports.Impression management using graphical resources in Brazilian company reports. Keylla Dennyse Celestino da Silva; Fernanda Fernandes Rodrigues; e César Augusto Tibúrcio Silva. Int. J. Accounting and Finance, Vol. 9, No. 1, 2019
Números de Brumadinho
É bem verdade que o assunto não é novo, já que o problema ocorreu em janeiro e a empresa já tinha divulgado uma informação anteriormente. Mas passados alguns meses, é possível perceber que o desastre ambiental ainda repercute no desempenho. E ainda irá afetar este desempenho nos próximos meses.
O principal número é a provisão que a empresa faz para cobrir os problemas causados pela barragem. Os números indicam um valor de 6 bilhões na DRE dos seis primeiros meses, sendo 4,5 relacionados com o primeiro trimestre (fonte: aqui). Este valor inclui os acordos na justiça, a compensação dos danos, multas e despesas. O fato de ser o segundo desastre ambiental em menos de quatro anos certamente afetou o valor da provisão (o outro desastre, da Samarco, a Vale fazia parte da joint-venture).
Já segundo o Valor o impacto seria de 23 bilhões! Eis o trecho:
O provisionamento de R$5,3 bilhões feito pela Vale no segundo trimestre devido ao rompimento da barragem em Brumadinho se somou aos 17,315 bilhões de provisões e despesas registrados pela empresa no primeiro trimestre. Contando outros R$621 milhões em despesas incorridas pela empresa no segundo trimestre, o acidente com a barragem causou até o momento impacto de R$23,236 bilhões no balanço da mineradora.
Confesso que não encontrei este valor de R$17,315 bilhões. Isto contraria até o valor divulgado pela empresa.
31 julho 2019
Muito trabalho para o IASB
Prever sucesso empresarial é difícil
Resumo:
We compare the absolute and relative performance of three approaches to predicting outcomes for entrants in a business plan competition in Nigeria: Business plan scores from judges, simple ad-hoc prediction models used by researchers, and machine learning approaches. We find that i) business plan scores from judges are uncorrelated with business survival, employment, sales, or profits three years later; ii) a few key characteristics of entrepreneurs such as gender, age, ability, and business sector do have some predictive power for future outcomes; iii) modern machine learning methods do not offer noticeable improvements; iv) the overall predictive power of all approaches is very low, highlighting the fundamental difficulty of picking competition winners.
Fonte: Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria
We compare the absolute and relative performance of three approaches to predicting outcomes for entrants in a business plan competition in Nigeria: Business plan scores from judges, simple ad-hoc prediction models used by researchers, and machine learning approaches. We find that i) business plan scores from judges are uncorrelated with business survival, employment, sales, or profits three years later; ii) a few key characteristics of entrepreneurs such as gender, age, ability, and business sector do have some predictive power for future outcomes; iii) modern machine learning methods do not offer noticeable improvements; iv) the overall predictive power of all approaches is very low, highlighting the fundamental difficulty of picking competition winners.
Fonte: Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria
Caixa e Equivalentes
O gráfico abaixo mostra a evolução, nos últimos meses, do Caixa e Equivalente de 278 empresas brasileiras.
O volume de caixa tem-se mantido estável nos últimos anos. Entretanto, o número é influenciado por grandes empresas. Usando somente a mediana temos:
A Petrobras, que chegou a ter quase 100 bilhões de reais em setembro de 2015. Este valor caiu para 54 bilhões em março de 2019 e 36 bilhões em junho de 2019.
30 julho 2019
Máquinas não vão dominar o mundo
Stephen Hawking envisioned an AI apocalypse and noted astronomer Sir Martin Rees envisions cyborgs on Mars. A tech analyst thinks robots should run for office. Never mind, Dilbert’s creator, Scott Adams, thinks we’ll soon be ruled by The Algorithm anyway. And cosmologist Max Tegmark explains how he thinks AI could end up running the world. It’s a cool apocalypse but does that make it more likely?
Here are some of the true limitations on machine intelligence, for the next time the subject comes up over coffee:
● Computer science professor Robert J. Marks points out that machine intelligence is much more sophisticated today than in the past but it hasn’t fundamentally changed: “A bigger computer would be like a bigger truck. All a truck can really do is haul things and all computers can really do is calculate. Limitations on computer performance are constrained by algorithmic information theory. According to the Church-Turing Thesis, anything done on the very fast computers of today could have been done—in principle—on Turing’s original 1930’s Turing machine. We can perform tasks faster today but the fundamental limitations of computing remain.”
● Software pioneer François Chollet points out that an intelligence is not capable of designing an intelligence greater than itself.
● Melanie Mitchell, Professor of Computer Science at Portland State University warns that machines do not understand what things mean. However powerful, they will always be vulnerable to malicious takeovers:
Numerous studies have demonstrated the ease with which hackers could, in principle, fool face- and object-recognition systems with specific minuscule changes to images, put inconspicuous stickers on a stop sign to make a self-driving car’s vision system mistake it for a yield sign or modify an audio signal so that it sounds like background music to a human but instructs a Siri or Alexa system to perform a silent command.
Melanie Mitchell, “Artificial Intelligence Hits the Barrier of Meaning” AT New York Times
Those who say that a system can be designed that is sophisticated enough to prevent that miss the point: The hacker is looking for a vulnerability due to the fact that the system only mimics understanding but does not possess it. To the extent that the system does not possess understanding, such points will probably always exist.
● Computer engineer Eric Holloway reminds us that a defining aspect of the human mind is its ability to create mutual information. You might understand a sign you have never seen before because you can guess, on your own, what someone might be trying to tell you. Machines operate according to randomness and determinism but Levin’s Law of independence conservation states that “no combination of random and deterministic processing can increase mutual information.”
● Software architect Brendan Dixon adds that human intelligence is not simply a matter of IQ; culture plays an important role. The geniuses who develop great ideas are working within a surrounding culture of other unique people with ideas. One can input a great deal of information into a system but the system isn’t a culture in the same way.
● Finally, physicist Alfredo Metere of the International Computer Science Institute (ICSI) insists that AI must deal in specifics but humans live in an indefinitely blurry world that is always changing:
AI is a bunch of mathematical models that need to be realised in some physical medium, such as, for example, programs that can be stored and run in a computer. No wizards, no magic. The moment we implement AI models as computer programs, we are sacrificing something, due to the fact that we must reduce reality to a bunch of finite bits that a computer can crunch on.Alfredo Metere, “AI will never conquer humanity. It’s too rational.” at Cosmos
So, given these limitations, is AI a threat to democracy? The main problem that neurosurgeon Michael Egnor sees is its obscurity. We often don’t know how AI is being used:
What algorithms does Google use when we search on political topics? We don’t know. It is inevitable that such searches are biased, perhaps deliberately, perhaps not… It is not far-fetched to imagine self-driving cars “choosing” routes that go past merchants who “advertise” surreptitiously, using the autonomous vehicles. How much would Mc Donald’s pay to route the cars and slow them down when they pass the Golden Arches? How much would a political party pay to skew a Google search on their candidates?
In short, the real concern is not that the machine will run the show but that the machine’s owners will run it and we won’t know exactly how they are doing it. They’ll say they don’t know how they are doing it either. It just somehow happened.
Assuming we get past that, non-hype experts think that our future is more likely to include coexisting with AI and robots than having our lives run by them:
Once people come to understand how limited today’s machine learning systems are, the exaggerated hopes they have aroused will evaporate quickly, warns Roger Schank, an AI expert who specialises in the psychology of learning. The result, he predicts, will be a new “AI winter” — a reference to the period in the late 1980s when disappointment over the progress of the technology led to a retreat from the field… David Mindell, a Massachusetts Institute of Technology professor who has written about the challenges of getting humans and robots to interact effectively, puts it most succinctly: “The computer science world still has a long way to go before it has a clue about how to deal with people.” Richard Waters, “Artificial intelligence: when humans coexist with robots” at Financial Times
And with that, of course, supercomputers are not going to be much of a help.
Fonte: aqui
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