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ELIZA effect

In computer science, the ELIZA effect is the tendency to project human traits — such as experience, semantic comprehension or empathy — into computer programs that have a textual interface. The effect is a category mistake that arises when the program's symbolic computations are described through terms such as "think", "know" or "understand."

History
The effect is named for ELIZA, the 1966 chatbot developed by MIT computer scientist Joseph Weizenbaum. When executing Weizenbaum's DOCTOR script, ELIZA simulated a Rogerian psychotherapist, largely by rephrasing the "patients replies as questions:

 * Human: Well, my boyfriend made me come here.
 * ELIZA: Your boyfriend made you come here?
 * Human: He says I'm depressed much of the time.
 * ELIZA: I am sorry to hear you are depressed.
 * Human: It's true. I'm unhappy.
 * ELIZA: Do you think coming here will help you not to be unhappy?

Though designed strictly as a mechanism to support "natural language conversation" with a computer, ELIZA's DOCTOR script was found to be surprisingly successful in eliciting emotional responses from users who, in the course of interacting with the program, began to ascribe understanding and motivation to the program's output. As Weizenbaum later wrote, "I had not realized ... that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people." Indeed, ELIZA's code had not been designed to evoke this reaction in the first place. Upon observation, researchers discovered users unconsciously assuming ELIZA's questions implied interest and emotional involvement in the topics discussed, even when they consciously knew that ELIZA did not simulate emotion.

Although the effect was first named in the 1960s, the tendency to understand mechanical operations in psychological terms was noted by Charles Babbage. In proposing what would later be called a carry-lookahead adder, Babbage remarked that he found such terms convenient for descriptive purposes, even though nothing more than mechanical action was meant.

Characteristics
In its specific form, the ELIZA effect refers only to "the susceptibility of people to read far more understanding than is warranted into strings of symbols—especially words—strung together by computers". A trivial example of the specific form of the Eliza effect, given by Douglas Hofstadter, involves an automated teller machine which displays the words "THANK YOU" at the end of a transaction. A naive observer might think that the machine is actually expressing gratitude; however, the machine is only printing a preprogrammed string of symbols.

More generally, the ELIZA effect describes any situation where, based solely on a system's output, users perceive computer systems as having "intrinsic qualities and abilities which the software controlling the (output) cannot possibly achieve" or "assume that [outputs] reflect a greater causality than they actually do". In both its specific and general forms, the ELIZA effect is notable for occurring even when users of the system are aware of the determinate nature of output produced by the system.

From a psychological standpoint, the ELIZA effect is the result of a subtle cognitive dissonance between the user's awareness of programming limitations and their behavior towards the output of the program.

Significance
The discovery of the ELIZA effect was an important development in artificial intelligence, demonstrating the principle of using social engineering rather than explicit programming to pass a Turing test.

ELIZA convinced some users into thinking that a machine was human. This shift in human-machine interaction marked progress in technologies emulating human behavior. Two groups of chatbots are distinguished by William Meisel as "general personal assistants" and "specialized digital assistants". General digital assistants have been integrated into personal devices, with skills like sending messages, taking notes, checking calendars, and setting appointments. Specialized digital assistants "operate in very specific domains or help with very specific tasks". Digital assistants that are programmed to aid productivity by assuming behaviors analogous to humans.

Weizenbaum considered that not every part of the human thought could be reduced to logical formalisms and that "there are some acts of thought that ought to be attempted only by humans". He also observed that we develop emotional involvement with machines if we interact with them as humans. When chatbots are anthropomorphized, they tend to portray gendered features as a way through which we establish relationships with the technology. "Gender stereotypes are instrumentalised to manage our relationship with chatbots" when human behavior is programmed into machines.

In the 1990s, Clifford Nass and Byron Reeves conducted a series of experiments establishing The Media Equation, demonstrating that people tend to respond to media as they would either to another person (by being polite, cooperative, attributing personality characteristics such as aggressiveness, humor, expertise, and gender) – or to places and phenomena in the physical world. Numerous subsequent studies that have evolved from the research in psychology, social science and other fields indicate that this type of reaction is automatic, unavoidable, and happens more often than people realize. Reeves and Nass (1996) argue that, "Individuals' interactions with computers, television, and new media are fundamentally social and natural, just like interactions in real life," (p. 5).

Feminized labor, or women's work, automated by anthropomorphic digital assistants reinforces an "assumption that women possess a natural affinity for service work and emotional labour". In defining our proximity to digital assistants through their human attributes, chatbots become gendered entities.

title: ELIZA effect


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Exponentiation by squaring

In mathematics and computer programming, exponentiating by squaring is a general method for fast computation of large positive integer powers of a number, or more generally of an element of a semigroup, like a polynomial or a square matrix. Some variants are commonly referred to as square-and-multiply algorithms or binary exponentiation. These can be of quite general use, for example in modular arithmetic or powering of matrices. For semigroups for which additive notation is commonly used, like elliptic curves used in cryptography, this method is also referred to as double-and-add.

Recursive version
The method is based on the observation that, for any integer $$n > 0$$, one has: $$ x^n= \begin{cases} x \, ( x^{2})^{(n - 1)/2}, & \mbox{if } n \mbox{ is odd} \\ (x^{2})^{n/2}, & \mbox{if } n \mbox{ is even} \end{cases} $$

If the exponent $n$ is zero then the answer is 1. If the exponent is negative then we can reuse the previous formula by rewriting the value using a positive exponent. That is, $$x^n = \left(\frac{1}{x}\right)^{-n}\,.$$

Together, these may be implemented directly as the following recursive algorithm:

In: an integer x; an integer n Out: xn  exp_by_squaring(x, n)    if n < 0 then return exp_by_squaring(1 / x, -n); else if n = 0 then return 1; else if n is even then return exp_by_squaring(x * x, n / 2); else if n is odd then return x * exp_by_squaring(x * x, (n - 1) / 2); end function

In each recursive call, the least significant digits of the binary representation of $n$ is removed. It follows that the number of recursive calls is $$\lceil \log_2 n\rceil,$$ the number of bits of the binary representation of $n$. So this algorithm computes this number of squares and a lower number of multiplication, which is equal to the number of $1$ in the binary representation of $n$. This logarithmic number of operations is to be compared with the trivial algorithm which requires $n − 1$ multiplications.

This algorithm is not tail-recursive. This implies that it requires an amount of auxiliary memory that is roughly proportional to the number of recursive calls -- or perhaps higher if the amount of data per iteration is increasing.

The algorithms of the next section use a different approach, and the resulting algorithms needs the same number of operations, but use an auxiliary memory that is roughly the same as the memory required to store the result.

With constant auxiliary memory
The variants described in this section are based on the formula
 * $$ yx^n=

\begin{cases} (yx) \, ( x^{2})^{(n - 1)/2}, & \mbox{if } n \mbox{ is odd} \\ y\,(x^{2})^{n/2}, & \mbox{if } n \mbox{ is even}. \end{cases} $$

If one applies recursively this formula, by starting with $y = 1$, one gets eventually an exponent equal to $0$, and the desired result is then the left factor.

This may be implemented as a tail-recursive function:

The iterative version of the algorithm also uses a bounded auxiliary space, and is given by

The correctness of the algorithm results from the fact that $$yx^n$$ is invariant during the computation; it is $$1\cdot x^n=x^n$$ at the beginning; and it is $$yx^1=xy $$ at the end.

These algorithms use exactly the same number of operations as the algorithm of the preceding section, but the multiplications are done in a different order.

Computational complexity
A brief analysis shows that such an algorithm uses $$\lfloor \log_2n\rfloor$$ squarings and at most $$\lfloor \log_2n\rfloor$$ multiplications, where $$\lfloor\;\rfloor$$ denotes the floor function. More precisely, the number of multiplications is one less than the number of ones present in the binary expansion of n. For n greater than about 4 this is computationally more efficient than naively multiplying the base with itself repeatedly.

Each squaring results in approximately double the number of digits of the previous, and so, if multiplication of two d-digit numbers is implemented in O(dk) operations for some fixed k, then the complexity of computing xn is given by

\sum\limits_{i=0}^{O(\log n)} \big(2^i O(\log x)\big)^k = O\big((n \log x)^k\big). $$

2k-ary method
This algorithm calculates the value of xn after expanding the exponent in base 2k. It was first proposed by Brauer in 1939. In the algorithm below we make use of the following function f(0) = (k, 0) and f(m) = (s, u), where m = u·2s with u odd.

Algorithm:

 * Input: An element x of G, a parameter k > 0, a non-negative integer $n = (n_{l−1}, n_{l−2}, ..., n_{0})_{2^{k}}|undefined$ and the precomputed values $$x^3, x^5, ..., x^{2^k-1}$$.

 * Output: The element xn in G

y := 1; i := l - 1 while i ≥ 0 do    (s, u) := f(ni) for j := 1 to k - s do y := y2    y := y * xu     for j := 1 to s do y := y2    i := i - 1 return y

For optimal efficiency, k should be the smallest integer satisfying

 * $$\lg n < \frac{k(k + 1) \cdot 2^{2k}}{2^{k+1} - k - 2} + 1.$$

Sliding-window method
This method is an efficient variant of the 2k-ary method. For example, to calculate the exponent 398, which has binary expansion (110 001 110)2, we take a window of length 3 using the 2k-ary method algorithm and calculate 1, x3, x6, x12, x24, x48, x49, x98, x99, x198, x199, x398. But, we can also compute 1, x3, x6, x12, x24, x48, x96, x192, x199, x398, which saves one multiplication and amounts to evaluating (110 001 110)2

Here is the general algorithm:

Algorithm:

 * Input: An element x of G, a non negative integer $n=(n_{l−1}, n_{l−2}, ..., n_{0})_{2}$, a parameter k > 0 and the pre-computed values $$x^3, x^5, ... ,x^{2^k-1}$$.

 * Output: The element xn ∈ G.

Algorithm:

y := 1; i := l - 1 while i > -1 do if ni = 0 then y := y2' i := i - 1 else s := max{i - k + 1, 0} while ns = 0 do s := s + 1 for h := 1 to i - s + 1 do y := y2        u := (ni, ni-1, ..., ns)2 y := y * xu        i := s - 1 return y

Montgomery's ladder technique
Many algorithms for exponentiation do not provide defence against side-channel attacks. Namely, an attacker observing the sequence of squarings and multiplications can (partially) recover the exponent involved in the computation. This is a problem if the exponent should remain secret, as with many public-key cryptosystems. A technique called "Montgomery's ladder" addresses this concern.

Given the binary expansion of a positive, non-zero integer n = (nk−1...n0)2 with nk−1 = 1, we can compute xn as follows: x1 = x; x2 = x2 for i = k - 2 to 0 do if ni = 0 then x2 = x1 * x2; x1 = x12 else x1 = x1 * x2; x2 = x22 return x1

The algorithm performs a fixed sequence of operations (up to log n): a multiplication and squaring takes place for each bit in the exponent, regardless of the bit's specific value. A similar algorithm for multiplication by doubling exists.

This specific implementation of Montgomery's ladder is not yet protected against cache timing attacks: memory access latencies might still be observable to an attacker, as different variables are accessed depending on the value of bits of the secret exponent. Modern cryptographic implementations use a "scatter" technique to make sure the processor always misses the faster cache.

Fixed-base exponent
There are several methods which can be employed to calculate xn when the base is fixed and the exponent varies. As one can see, precomputations play a key role in these algorithms.

Yao's method
Yao's method is orthogonal to the $2^{k}$-ary method where the exponent is expanded in radix $b = 2^{k}$ and the computation is as performed in the algorithm above. Let $n$, $n_{i}$, $b$, and $b_{i}$ be integers.

Let the exponent $n$ be written as
 * $$ n = \sum_{i=0}^{w-1} n_i b_i,$$

where $$0 \leqslant n_i < h$$ for all $$i \in [0, w-1]$$.

Let $x_{i} = x^{b_{i}}|undefined$.

Then the algorithm uses the equality
 * $$x^n = \prod_{i=0}^{w-1} x_i^{n_i} = \prod_{j=1}^{h-1} \bigg[\prod_{n_i=j} x_i\bigg]^j.$$

Given the element $x$ of $G$, and the exponent $n$ written in the above form, along with the precomputed values $x^{b_{0}}...x^{b_{w−1}}|undefined$, the element $x^{n}$ is calculated using the algorithm below:

y = 1, u = 1, j = h - 1 while j > 0 do for i = 0 to w - 1 do if ni = j then u = u × xbi y = y × u    j = j - 1 return y

If we set $h = 2^{k}$ and $b_{i} = h^{i}$, then the $n_{i}$ values are simply the digits of $n$ in base $h$. Yao's method collects in u first those $x_{i}$ that appear to the highest power $h - 1$; in the next round those with power $h - 2$ are collected in $u$ as well etc. The variable y is multiplied $h - 1$ times with the initial $u$, $h - 2$ times with the next highest powers, and so on. The algorithm uses $w + h - 2$ multiplications, and $w + 1$ elements must be stored to compute $x^{n}$.

Euclidean method
The Euclidean method was first introduced in Efficient exponentiation using precomputation and vector addition chains by P.D Rooij.

This method for computing $$x^n$$ in group $G$, where $n$ is a natural integer, whose algorithm is given below, is using the following equality recursively:
 * $$x_0^{n_0} \cdot x_1^{n_1} = \left(x_0 \cdot x_1^q\right)^{n_0} \cdot x_1^{n_1 \mod n_0},$$

where $$q = \left\lfloor \frac{n_1}{n_0} \right\rfloor$$. In other words, a Euclidean division of the exponent $n_{1}$ by $n_{0}$ is used to return a quotient $q$ and a rest $n_{1} mod n_{0}$.

Given the base element $x$ in group $G$, and the exponent $$n$$ written as in Yao's method, the element $$x^n$$ is calculated using $$l$$ precomputed values $$x^{b_0}, ..., x^{b_{l_i}}$$ and then the algorithm below.

Begin loop Find $M \in [0, l - 1]$, such that $\forall i \in [0, l - 1], n_M \ge n_i$. Find $N \in \big([0, l - 1] - M\big)$, such that $\forall i \in \big([0, l - 1] - M\big), n_N \ge n_i$. Break loop if $n_N = 0$. Let $q = \lfloor n_M / n_N \rfloor$, and then let $n_N = (n_M \bmod n_N)$. Compute recursively $x_M^q$, and then let $x_N = x_N \cdot x_M^q$. End loop; Return $x^n = x_M^{n_M}$.

The algorithm first finds the largest value among the $n_{i}$ and then the supremum within the set of $( n_{i} \ i ≠ M )$. Then it raises $x_{M}$ to the power $q$, multiplies this value with $x_{N}$, and then assigns $x_{N}$ the result of this computation and $n_{M}$ the value $n_{M}$ modulo $n_{N}$.

Further applications
The approach also works with semigroups that are not of characteristic zero, for example allowing fast computation of large exponents modulo a number. Especially in cryptography, it is useful to compute powers in a ring of integers modulo $q$. For example, the evaluation of

would take a very long time and much storage space if the naïve method of computing $13789^{722341} (mod 2345) = 2029$ and then taking the remainder when divided by 2345 were used. Even using a more effective method will take a long time: square 13789, take the remainder when divided by 2345, multiply the result by 13789, and so on.

Applying above exp-by-squaring algorithm, with "*" interpreted as $13789^{722341}$ (that is, a multiplication followed by a division with remainder) leads to only 27 multiplications and divisions of integers, which may all be stored in a single machine word. Generally, any of these approaches will take fewer than $x * y = xy mod 2345$ modular multiplications.

The approach can also be used to compute integer powers in a group, using either of the rules

The approach also works in non-commutative semigroups and is often used to compute powers of matrices.

More generally, the approach works with positive integer exponents in every magma for which the binary operation is power associative.

Signed-digit recoding
In certain computations it may be more efficient to allow negative coefficients and hence use the inverse of the base, provided inversion in $G$ is "fast" or has been precomputed. For example, when computing $2log2(722340) ≤ 40$, the binary method requires $Power(x, −n) = Power(x^{−1}, n)$ multiplications and $Power(x, −n) = (Power(x, n))^{−1}$ squarings. However, one could perform $k$ squarings to get $x^{2^{k}−1}$ and then multiply by $k−1$ to obtain $k−1$.

To this end we define the signed-digit representation of an integer $n$ in radix $b$ as
 * $$n = \sum_{i=0}^{l-1} n_i b^i \text{ with  } |n_i| < b.$$

Signed binary representation corresponds to the particular choice $x^{2^{k}}|undefined$ and $$n_i \in \{-1, 0, 1\}$$. It is denoted by $$(n_{l-1} \dots n_0)_s$$. There are several methods for computing this representation. The representation is not unique. For example, take $x^{−1}$: two distinct signed-binary representations are given by $$(10\bar 1 1100\bar 1 10)_s$$ and $$(100\bar 1 1000\bar 1 0)_s$$, where $$\bar 1$$ is used to denote $x^{2^{k}−1}$. Since the binary method computes a multiplication for every non-zero entry in the base-2 representation of $n$, we are interested in finding the signed-binary representation with the smallest number of non-zero entries, that is, the one with minimal Hamming weight. One method of doing this is to compute the representation in non-adjacent form, or NAF for short, which is one that satisfies $$n_i n_{i+1} = 0 \text{ for all } i \geqslant 0$$ and denoted by $$(n_{l-1} \dots n_0)_\text{NAF}$$. For example, the NAF representation of 478 is $$(1000\bar 1 000\bar 1 0)_\text{NAF}$$. This representation always has minimal Hamming weight. A simple algorithm to compute the NAF representation of a given integer $$n = (n_l n_{l-1} \dots n_0)_2$$ with $$n_l = n_{l-1} = 0$$ is the following:

$c_0=0$ for $b = 2$ to $n = 478$ do  $c_{i+1} = \left\lfloor\frac{1}{2}(c_i + n_i + n_{i+1})\right\rfloor$ $n_i' = c_i + n_i - 2c_{i+1}$ return $(n_{l-1}' \dots n_0')_\text{NAF}$

Another algorithm by Koyama and Tsuruoka does not require the condition that $$n_i = n_{i+1} = 0$$; it still minimizes the Hamming weight.

Alternatives and generalizations
Exponentiation by squaring can be viewed as a suboptimal addition-chain exponentiation algorithm: it computes the exponent by an addition chain consisting of repeated exponent doublings (squarings) and/or incrementing exponents by one (multiplying by x) only. More generally, if one allows any previously computed exponents to be summed (by multiplying those powers of x), one can sometimes perform the exponentiation using fewer multiplications (but typically using more memory). The smallest power where this occurs is for n = 15:

 * $$x^{15} = x \times (x \times [x \times x^2]^2)^2$$ (squaring, 6 multiplies),
 * $$x^{15} = x^3 \times ([x^3]^2)^2$$ (optimal addition chain, 5 multiplies if x3 is re-used).

In general, finding the optimal addition chain for a given exponent is a hard problem, for which no efficient algorithms are known, so optimal chains are typically used for small exponents only (e.g. in compilers where the chains for small powers have been pre-tabulated). However, there are a number of heuristic algorithms that, while not being optimal, have fewer multiplications than exponentiation by squaring at the cost of additional bookkeeping work and memory usage. Regardless, the number of multiplications never grows more slowly than Θ(log n), so these algorithms improve asymptotically upon exponentiation by squaring by only a constant factor at best.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: Exponentiation by squaring


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Exon

An exon is any part of a gene that will form a part of the final mature RNA produced by that gene after introns have been removed by RNA splicing. The term exon refers to both the DNA sequence within a gene and to the corresponding sequence in RNA transcripts. In RNA splicing, introns are removed and exons are covalently joined to one another as part of generating the mature RNA. Just as the entire set of genes for a species constitutes the genome, the entire set of exons constitutes the exome.

History
The term exon derives from the expressed region and was coined by American biochemist Walter Gilbert in 1978: "The notion of the cistron... must be replaced by that of a transcription unit containing regions which will be lost from the mature messenger – which I suggest we call introns (for intragenic regions) – alternating with regions which will be expressed – exons."

This definition was originally made for protein-coding transcripts that are spliced before being translated. The term later came to include sequences removed from rRNA and tRNA, and other ncRNA and it also was used later for RNA molecules originating from different parts of the genome that are then ligated by trans-splicing.

Contribution to genomes and size distribution
Although unicellular eukaryotes such as yeast have either no introns or very few, metazoans and especially vertebrate genomes have a large fraction of non-coding DNA. For instance, in the human genome only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. This can provide a practical advantage in omics-aided health care (such as precision medicine) because it makes commercialized whole exome sequencing a smaller and less expensive challenge than commercialized whole genome sequencing. The large variation in genome size and C-value across life forms has posed an interesting challenge called the C-value enigma.

Across all eukaryotic genes in GenBank, there were (in 2002), on average, 5.48 exons per protein coding gene. The average exon encoded 30-36 amino acids. While the longest exon in the human genome is 11555 bp long, several exons have been found to be only 2 bp long. A single-nucleotide exon has been reported from the Arabidopsis genome. In humans, like protein coding mRNA, most non-coding RNA also contain multiple exons

Structure and function

In protein-coding genes, the exons include both the protein-coding sequence and the 5′- and 3′-untranslated regions (UTR). Often the first exon includes both the 5′-UTR and the first part of the coding sequence, but exons containing only regions of 5′-UTR or (more rarely) 3′-UTR occur in some genes, i.e. the UTRs may contain introns. Some non-coding RNA transcripts also have exons and introns.

Mature mRNAs originating from the same gene need not include the same exons, since different introns in the pre-mRNA can be removed by the process of alternative splicing.

Exonization is the creation of a new exon, as a result of mutations in introns.

Experimental approaches using exons
Exon trapping or 'gene trapping' is a molecular biology technique that exploits the existence of the intron-exon splicing to find new genes. The first exon of a 'trapped' gene splices into the exon that is contained in the insertional DNA. This new exon contains the ORF for a reporter gene that can now be expressed using the enhancers that control the target gene. A scientist knows that a new gene has been trapped when the reporter gene is expressed.

Splicing can be experimentally modified so that targeted exons are excluded from mature mRNA transcripts by blocking the access of splice-directing small nuclear ribonucleoprotein particles (snRNPs) to pre-mRNA using Morpholino antisense oligos. This has become a standard technique in developmental biology. Morpholino oligos can also be targeted to prevent molecules that regulate splicing (e.g. splice enhancers, splice suppressors) from binding to pre-mRNA, altering patterns of splicing.

Common misuse of the term
Common incorrect uses of the term exon are that 'exons code for protein', or 'exons code for amino-acids' or 'exons are translated'. However, these sorts of definitions only cover protein-coding genes, and omit those exons that become part of a non-coding RNA or the untranslated region of an mRNA. Such incorrect definitions still occur in overall reputable secondary sources.

title: Exon


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Exxon Valdez oil spill

The Exxon Valdez oil spill was a major environmental disaster that made worldwide headlines in the spring of 1989 and occurred in Alaska's Prince William Sound on March 24, 1989. The spill occurred when Exxon Valdez, an oil supertanker owned by Exxon Shipping Company, bound for Long Beach, California, struck Prince William Sound's Bligh Reef, 6 mi west of Tatitlek, Alaska at 12:04 a.m. The tanker spilled approximately 10.8 e6USgal (or 37,000 tonnes) of crude oil over the next few days.

The Exxon Valdez spill is the second largest in U.S. waters, after the 2010 Deepwater Horizon oil spill, in terms of volume of oil released. Prince William Sound's remote location, accessible only by helicopter, plane, or boat, made government and industry response efforts difficult and made existing response plans especially hard to implement. The region is a habitat for salmon, sea otters, seals, and seabirds. The oil, extracted from the Prudhoe Bay Oil Field, eventually affected 1300 mi of coastline, of which 200 mi were heavily or moderately oiled.

Spill
Exxon Valdez was carrying 53.1 e6USgal of oil, of which approximately 10.8 e6USgal were spilled into the Prince William Sound.

The ship docked at the Valdez Marine Terminal at 11:30 p.m. on March 22, 1989. Loading of crude oil was completed late in the day on the 23rd. The tanker left the terminal at 9:12 p.m., March 23, 1989 (the deck log shows that it was clear of the dock at 9:21p.m.), loaded with 53,094,510 gallons (1,264,155 barrels) of crude oil. Captain Joseph Hazelwood retired to his cabin at 9:25p.m. Harbor pilot William Murphy and Third Mate Gregory Cousins were accompanied by a single tug for the passage through the Valdez Narrows – a journey of about 7 miles. The pilot left the bridge shortly after the vessel left the narrows, at 11:24p.m. At this point, the captain was called to the bridge. Cousins helped the pilot disembark from the vessel, leaving the captain as the only officer on the bridge. At 11:25p.m. Exxon Valdez reported that the pilot had left. The third mate advised traffic control and decided to deviate from the predetermined traffic lane to avoid small icebergs; a common occurrence since the Columbia Glacier calved such icebergs nearby. The vessel was placed on a due south course and set on autopilot. At 11:47p.m. the vessel left the traffic lane's eastern boundary.

Third Mate Cousins had been on duty for 6 hours and was scheduled to be relieved by Second Mate Lloyd LeCain Jr. However, due to the long hours that the second mate had worked, Cousins was reluctant to wake him, and remained on duty. Cousins was the only officer on the bridge for most of the night, in violation of company policy. At around midnight on March 24 Cousins began to maneuver the vessel into the traffic lanes. At the same time, the lookout reported that the Bligh Reef light appeared far off the starboard bow at 45 degrees – this was problematic given that the light should have been off the port side. Cousins ordered a course change as the ship was in danger. Captain Hazelwood was phoned by Cousins, but before their conversation could finish, the ship grounded. At 12:04a.m., accompanied by what the helmsman and Cousins described as "a bumpy ride" and "six very sharp jolts" respectively, the ship ran aground on Bligh Reef.

Carried by its own momentum, the ship ended up perched on its middle on a pinnacle of rock. 8 out of 11 cargo holds were punctured. 5.8 million gallons of oil drained from the ship within 3 hours and 15 minutes. 30 minutes after numerous attempts to dislodge the ship under her own power, Captain Hazelwood radioed the Coast Guard informing them of the grounding. For more than 45 minutes after the grounding, the captain attempted to maneuver free of the reef despite being informed by First Mate James Kunkel that the vessel was not structurally sound without the reef supporting it.

Multiple factors have been identified as contributing to the incident:

 * Exxon Shipping Company failed to supervise the master (ship's captain) and provide a rested and sufficient crew for Exxon Valdez. The NTSB found this practice was widespread throughout the industry, prompting a safety recommendation to Exxon and to the industry.
 * The third mate failed to properly maneuver the vessel, possibly due to fatigue or excessive workload.
 * Exxon Shipping Company failed to properly maintain the Raytheon Collision Avoidance System (RAYCAS) radar, which, if functional, would have indicated to the third mate an impending collision with the Bligh Reef by detecting the radar reflector placed on the next rock inland from Bligh Reef for the purpose of keeping ships on course. This cause was brought forward by Greg Palast and is not presented in the official accident report.

Captain Hazelwood, who was widely reported to have been drinking heavily that night, was not at the controls when the ship struck the reef. Exxon blamed Hazelwood for the grounding of the tanker, but he accused the corporation of making him a scapegoat. In a 1990 trial he was charged with criminal mischief, reckless endangerment, and piloting a vessel while intoxicated, but was cleared of the three charges. He was convicted of misdemeanor negligent discharge of oil. 21 witnesses testified that he did not appear to be under the influence of alcohol around the time of the accident.

Journalist Greg Palast stated in 2008: "Forget the drunken skipper fable. As to Captain Joe Hazelwood, he was below decks, sleeping off his bender. At the helm, the third mate may never have collided with Bligh Reef had he looked at his RAYCAS radar. But the radar was not turned on. In fact, the tanker's radar was left broken and disabled for more than a year before the disaster, and Exxon management knew it. It was just too expensive to fix and operate."

Other factors, according to an MIT course entitled "Software System Safety" by Professor Nancy G. Leveson, included:
 * 1) Ships were not informed that the previous practice of the Coast Guard tracking ships out to Bligh Reef had ceased.
 * 2) The oil industry promised, but never installed, state-of-the-art iceberg monitoring equipment.
 * 3) Exxon Valdez was sailing outside the normal sea lane to avoid small icebergs thought to be in the area.

This disaster resulted in International Maritime Organization introducing comprehensive marine pollution prevention rules (MARPOL) through various conventions. The rules were ratified by member countries and, under International Ship Management rules, the ships are being operated with a common objective of "safer ships and cleaner oceans."
 * 1) Coast Guard vessel inspections in Valdez were not performed, and the number of staff was reduced.
 * 2) Lack of available equipment and personnel hampered the spill cleanup.

In 2009, Captain Hazelwood offered a "heartfelt apology" to the people of Alaska, suggesting he had been wrongly blamed for the disaster: "The true story is out there for anybody who wants to look at the facts, but that's not the sexy story and that's not the easy story," he said. Hazelwood said he felt Alaskans always gave him a fair shake.

Clean-up and major effects

Chemical dispersant, a surfactant and solvent mixture, was applied to the slick by a private company on March 24 with a helicopter, but the helicopter missed the target area. Scientific data on its toxicity were either thin or incomplete. In addition, public acceptance of new, widespread chemical treatment was lacking. Landowners, fishing groups, and conservation organizations questioned the use of chemicals on hundreds of miles of shoreline when other alternatives might have been available."

According to a report by David Kirby for TakePart, the main component of the Corexit formulation used during cleanup, 2-butoxyethanol, was identified as "one of the agents that caused liver, kidney, lung, nervous system, and blood disorders among cleanup crews in Alaska following the 1989 Exxon Valdez spill". It is now known that while 2-butoxyethanol is indeed a respiratory irritant that can be acutely toxic, animal studies did not find it to be mutagenic, and no studies suggest it to be a human carcinogen.

Mechanical cleanup was started shortly afterward using booms and skimmers, but the skimmers were not readily available during the first 24 hours following the spill, and thick oil and kelp tended to clog the equipment. Despite civilian insistence for a complete cleanup, only 10% of total oil was actually completely cleaned. Exxon was widely criticized for its slow response to cleaning up the disaster and John Devens, the mayor of Valdez, said his community felt betrayed by Exxon's inadequate response to the crisis. More than 11,000 Alaska residents, along with some Exxon employees, worked throughout the region to try to restore the environment.

Though the clean-up effort was diligent it failed to contain the majority of the oil that had spilled and that has been blamed heavily upon Exxon. On November 26, 1984 Ronald A. Kreizenbeck (Director, Alaska Operations Office) informed the Coast Guard that the EPA suspected, due to a recent site-visitation during an 'Annual Marine Drill' that the Port of Valdez was not prepared to "efficiently respond to a major spill event". In the letter, he stated that "[it] appears that the Vikoma boom and/or deployment vessels used may not be adequate to handle the harsh environmental conditions of Port Valdez".

Because Prince William Sound contained many rocky coves where the oil was collected, the decision was made to displace it with high-pressure hot water. However, this also displaced and destroyed the microbial populations on the shoreline; many of these organisms (e.g. plankton) are the basis of the coastal marine food chain, and others (e.g., certain bacteria and fungi) are capable of facilitating the biodegradation of oil. At the time, both scientific advice and public pressure was to clean everything, but since then, a much greater understanding of natural and facilitated remediation processes has developed, due somewhat in part to the opportunity presented for study by the Exxon Valdez spill.

Both long-term and short-term effects of the oil spill have been studied. Immediate effects include the deaths of between 100,000 and 250,000 seabirds, at least 2,800 sea otters, approximately 12 river otters, 300 harbor seals, 247 bald eagles, and 22 orcas, and an unknown number of salmon and herring.

Nine years after the disaster, evidence of negative oil spill effects on marine birds was found in the following species: cormorants, goldeneyes, mergansers, murres and pigeon guillemots.

Although the volume of oil has declined considerably, with oil remaining only about 0.14–0.28% of the original spilled volume, studies suggest that the area of oiled beach has changed little since 1992. A study by the National Marine Fisheries Service, NOAA in Juneau, determined that by 2001 approximately 90 tonnes of oil remained on beaches in Prince William Sound in the sandy soil of the contaminated shoreline, with annual loss rates declining from 68% per year prior to 1992, to 4% per year after 2001.

The remaining oil lasting far longer than anticipated has resulted in more long-term losses of species than had been expected. Laboratory experiments found that at levels as low as one part per billion, polycyclic aromatic hydrocarbons are toxic for salmon and herring eggs. Species as diverse as sea otters, harlequin ducks, and orcas suffered immediate and long-term losses. Oiled mussel beds and other tidal shoreline habitats may take up to 30 years to recover.

ExxonMobil denied concerns over the remaining oil, stating that they anticipated the remaining fraction would not cause long-term ecological impacts. According to the conclusions of ExxonMobil's study: "We've done 350 peer-reviewed studies of Prince William Sound, and those studies conclude that Prince William Sound has recovered, it's healthy and it's thriving."

On March 24, 2014, the twenty-fifth anniversary of the spill, NOAA scientists reported that some species seem to have recovered, with the sea otter the latest creature to return to pre-spill numbers. Scientists who have monitored the spill area for the last 25 years report that concern remains for one of two pods of local orca whales, with fears that one pod may eventually die out. Federal scientists estimate that between 16,000 and 21,000 US gallons (61 to 79 m3) of oil remains on beaches in Prince William Sound and up to 450 miles (725 km) away. Some of the oil does not appear to have biodegraded at all. A USGS scientist who analyses the remaining oil along the coastline states that it remains among rocks and between tide marks. "The oil mixes with seawater and forms an emulsion...Left out, the surface crusts over but the inside still has the consistency of mayonnaise – or mousse." Alaska state senator Berta Gardner is urging Alaskan politicians to demand that the US government force ExxonMobil to pay the final $92 million (£57 million) still owed from the court settlement. The major part of the money would be spent to finish cleaning up oiled beaches and attempting to restore the crippled herring population.

As of 2012, the indirect and long-term sublethal effects of oil on shorebirds had been measured in relatively few studies.

Litigation and cleanup costs

In October 1989, Exxon filed a suit against the State of Alaska, claiming that the state had interfered with Exxon's attempts to clean up the spill by refusing to approve the use of dispersant chemicals until the night of the 26th. The State of Alaska disputed this claim, stating that there was a long-standing agreement to allow the use of dispersants to clean up spills, thus Exxon did not require permission to use them, and that, in fact, Exxon had not had enough dispersant on hand to effectively handle a spill of the size created by Exxon Valdez.

Exxon filed claims in October 1990 against the Coast Guard, asking to be reimbursed for cleanup costs and damages awarded to plaintiffs in any lawsuits filed by the State of Alaska or the federal government against Exxon. The company claimed that the Coast Guard was "wholly or partially responsible" for the spill, because they had granted mariners' licenses to the crew of the Valdez, and because they had given Exxon Valdez permission to leave regular shipping lanes to avoid ice. They also reiterated the claim that the Coast Guard had delayed cleanup by refusing to give permission to immediately use chemical dispersants on the spill.

Also, in 1991, Exxon made a quiet, separate financial settlement of damages with a group of seafood producers known as the Seattle Seven for the disaster's effect on the Alaskan seafood industry. The agreement granted $63.75 million to the Seattle Seven, but stipulated that the seafood companies would have to repay almost all of any punitive damages awarded in other civil proceedings. The $5 billion in punitive damages was awarded later, and the Seattle Seven's share could have been as high as $750 million if the damages award had held. Other plaintiffs have objected to this secret arrangement, and when it came to light, Judge Holland ruled that Exxon should have told the jury at the start that an agreement had already been made, so the jury would know exactly how much Exxon would have to pay.

In the case of Exxon v. Baker, an Anchorage jury awarded $287 million for actual damages and $5 billion for punitive damages. To protect itself in case the judgment was affirmed, Exxon obtained a $4.8 billion credit line from J.P. Morgan & Co., who created the first modern credit default swap so that they would not have to hold as much money in reserve against the risk of Exxon's default.

Meanwhile, Exxon appealed the ruling, and the 9th U.S. Circuit Court of Appeals ordered the trial judge, Russel Holland, to reduce the punitive damages. On December 6, 2002, Holland announced that he had reduced the damages to $4 billion, which he concluded was justified by the facts of the case and was not grossly excessive. Exxon appealed again and the case returned to Holland to be reconsidered in light of a recent Supreme Court ruling in a similar case. Holland increased the punitive damages to $4.5 billion, plus interest.

After more appeals, in December 2006 the damages award was cut to $2.5 billion. The court of appeals cited recent Supreme Court rulings relative to limits on punitive damages.

Exxon appealed again. On May 23, 2007, the 9th Circuit Court of Appeals denied ExxonMobil's request for a third hearing and let stand its ruling that Exxon owed $2.5 billion in punitive damages. Exxon then appealed to the Supreme Court, which agreed to hear the case. On February 27, 2008, the Supreme Court heard oral arguments. Justice Samuel Alito, who at the time owned between $100,000 and $250,000 in Exxon stock, recused himself from the case. In a decision issued June 25, 2008, written by Justice David Souter, the court vacated the $2.5 billion award and remanded the case back to the lower court, finding that the damages were excessive with respect to maritime common law. Exxon's actions were deemed "worse than negligent but less than malicious." The punitive damages were further reduced to an amount of $507.5 million. The Court's ruling was that maritime punitive damages should not exceed the compensatory damages, supported by a precedent dating from 1818. Senate Judiciary Committee Chairman Patrick J. Leahy has decried the ruling as "another in a line of cases where this Supreme Court has misconstrued congressional intent to benefit large corporations."

Exxon's official position was that punitive damages greater than $25 million were not justified because the spill resulted from an accident, and because Exxon spent an estimated $2 billion cleaning up the spill and a further $1 billion to settle related civil and criminal charges. Attorneys for the plaintiffs contended that Exxon bore responsibility for the accident because the company "put a drunk in charge of a tanker in Prince William Sound." Exxon recovered a significant portion of clean-up and legal expenses through insurance claims associated with the grounding of Exxon Valdez.

As of December 15, 2009, Exxon had paid the entire $507.5 million in punitive damages, including lawsuit costs, plus interest, which were further distributed to thousands of plaintiffs. This amount was one-tenth of the original punitive damages, Exxon remained hugely profitable, the process of payment was drawn out over decades, and long term damage continues and is not funded by Exxon. Hence, the Exxon spill is often cited as shorthand for corporate responsibility for societal damage not being enforced adequately.

Coast Guard report
A 1989 report by the Coast Guard's U.S. National Response Center summarized the event and made many recommendations, including that neither Exxon, Alyeska Pipeline Service Company, the State of Alaska, nor the federal government were prepared for a spill of this magnitude.

Oil Pollution Act of 1990
In response to the spill, the United States Congress passed the Oil Pollution Act of 1990 (OPA). The legislation included a clause that prohibits any vessel that, after March 22, 1989, has caused an oil spill of more than 1 e6USgal in any marine area, from operating in Prince William Sound.

In April 1998, the company argued in a legal action against the federal government that the ship should be allowed back into Alaskan waters. Exxon claimed OPA was effectively a bill of attainder, a regulation that was unfairly directed at Exxon alone. In 2002, the 9th Circuit Court of Appeals ruled against Exxon. As of 2002, OPA had prevented 18 ships from entering Prince William Sound.

OPA also set a schedule for the gradual phase-in of a double hull design, providing an additional layer between the oil tanks and the ocean. While a double hull would likely not have prevented the Exxon Valdez disaster, a Coast Guard study estimated that it would have cut the amount of oil spilled by 60 percent.

Exxon Valdez was towed to San Diego, arriving on July 10. Repairs began on July 30. Approximately 1600 ST of steel were removed and replaced. In June 1990, the tanker, renamed Exxon Mediterranean, left the harbor after $30 million of repairs. In 1993, owned by SeaRiver Maritime, it was named S/R Mediterranean, then in 2005 Mediterranean. In 2008 the vessel was acquired by a Hong Kong company that operated her as Dong Fang Ocean, then in 2011 renamed her Oriental Nicety. In August 2012, she was beached at Dalian, China, and dismantled.

Alaska regulations
In the aftermath of the spill, Alaska governor Steve Cowper issued an executive order requiring two tugboats to escort every loaded tanker from Valdez out through Prince William Sound to Hinchinbrook Entrance. As the plan evolved in the 1990s, one of the two routine tugboats was replaced with a 210 ft Escort Response Vehicle (ERV). Tankers at Valdez are no longer single-hulled. Congress enacted legislation requiring all tankers to be double-hulled as of 2015.

Economic and Native impact
In 1991, following the collapse of populations of local marine species (particularly clams, herring, and seals), the Chugach Alaska Corporation, an Alaska Native Corporation, filed for Chapter 11 bankruptcy protection. It has since recovered.

According to several studies funded by the state of Alaska, the spill had both short-term and long-term economic effects. These included the loss of recreational sports, fisheries, reduced tourism, and an estimate of what economists call "existence value", which is the value to the public of a pristine Prince William Sound.

The economy of the city of Cordova, Alaska was adversely affected after the spill damaged stocks of salmon and herring in the area. The village of Chenega was transformed into an emergency base and media outlet. The local villagers had to cope with a tripling of their population from 80 to 250. When asked how they felt about the situation, a village councilor noted that they were too shocked and busy to be depressed; others emphasized the human costs of leaving children unattended while their parents worked to clean up. Many Alaska Natives were worried that too much time was spent on the fishery and not enough on the land that supports subsistence hunting.

In 2010, CNN reported on studies concluding that many oil spill cleanup workers involved in the Exxon Valdez response had subsequently become sick, and warned those exposed to the Deepwater Horizon oil spill to take heed. Anchorage lawyer Dennis Mestas found that this was true for 6,722 of 11,000 worker files he was able to inspect, despite access to the records being controlled by Exxon. Exxon denied this in a statement to CNN: "After 20 years, there is no evidence suggesting that either cleanup workers or the residents of the communities affected by the Valdez spill have had any adverse health effects as a result of the spill or its cleanup." Environmental activists and State officials became concerned that BP would use similar techniques to minimize liability and de-emphasize health impacts: "the symptoms being reported in the Gulf states are the same ones that hit workers in Alaska. And just like then, people with their backs against the wall financially are flocking to the take jobs with the cleanup... I'm feeling like BP is forcing them into this situation where BP holds all the cards, and BP is letting these workers get sick"

Reactions
In 1992, Exxon released a video titled Scientists and the Alaska Oil Spill for distribution to schools. Critics said the video misrepresented the clean-up process.

In December 1994, the Unabomber assassinated Burson-Marsteller executive Thomas J. Mosser, accusing him of having "helped Exxon clean up its public image after the Exxon Valdez incident".

In popular culture
Several weeks after the spill, Saturday Night Live aired a pointed sketch featuring Kevin Nealon, Phil Hartman, and Victoria Jackson as cleanup workers struggling to scrub the oil off of animals and rocks on a beach in Prince William Sound.

In the Rocko's Modern Life episode, "Rocko's Happy Sack", Rocko and his dog, Spunky are grocery shopping when the announcer informs everyone of a "spill in the seafood section", represented by a giant oil tanker labeled "Noxxon Valdez".

In the 1995 film Waterworld, Exxon Valdez is the flagship of the movie's villain, "The Deacon," the leader of a band of scavenging raiders. In the ship is a portrait of their patron saint, Joseph Hazelwood.

Free Willy 2: The Adventure Home, sequel to Free Willy, contained an oil spill plotline that echoes the Exxon Valdez oil spill.

In the second Forrest Gump novel, Gump and Co. by Winston Groom, Gump commandeers Exxon Valdez and accidentally crashes it.

Composer Jonathan Larson wrote a song called "Iron Mike" about the oil spill. The song is written in the style of a sea shanty. It was first professionally recorded by George Salazar for the album The Jonathan Larson Project.

The 1992 made-for-television film Dead Ahead: The Exxon Valdez Disaster, produced by HBO, dramatized the oil spill disaster.

In season 2, episode 8, of Breaking Bad, entitled "Better Call Saul", Walter White tells Jesse Pinkman that Jesse's friend Badger, who had been caught in a drug deal with their methamphetamine and placed under arrest, is going to spill [information] like the Exxon Valdez.

title: Exxon Valdez oil spill


text:
Édouard de Pomiane

Édouard Alexandre de Pomiane, sometimes Édouard Pozerski (20 April 1875 – 26 January 1964), was a French scientist, radio broadcaster and food writer. His parents emigrated from Congress Poland in 1863 after the January Uprising, changed their name from Pozerski to de Pomiane, and became French citizens.

De Pomiane worked as a physician at the Institut Pasteur in Paris, where he gave Félix d'Herelle a place to work on bacteriophages.

His best known works that have been translated into English are Cooking in Ten Minutes and Cooking with Pomiane. His writing was remarkable in its time for its directness (he frequently uses a strange second-person voice, telling you—the reader—what you are seeing and smelling as you follow a recipe) and for his general disdain for upper-class elaborate French cuisine. He travelled widely and quite a few of his recipes are from abroad. His recipes often take pains to demystify cooking by explaining the chemical processes at work.

He was a founding member of the Académie des Gastronomes in 1928, with the high rank of chair no. 5 Louis Pasteur. 1940 was the age of retirement from the Pasteur Institute, but he continued his work in a small laboratory made for him in the attic. His teaching at the Scientific Institute of Food Hygiene ended in 1943.

Books
"Vingt Plats Qui Donnent Goutte"IMG_7221.jpeg 1935 edition.
 * La Cuisine en dix minutes, ou l'Adaptation au rythme moderne (1930) ISBN 0-571-13599-4
 * Also translated as Cooking in ten minutes : The adaptation to the rhythm of our time ISBN 978-1-897959-61-9
 * Cooking with Pomiane ISBN 0-340-59937-5

title: Édouard de Pomiane